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In today's globalized agricultural system, information leakage of agricultural biological risk factors can lead to business risks and public panic, jeopardizing corporate reputation. To solve the above problems, this study constructs a blockchain network for agricultural product biological risk traceability based on agricultural product biological risk factor data to achieve traceability of biological risk traceability data of agricultural product supply chain to meet the sustainability challenges. To guarantee the secure and flexible sharing of agricultural product biological risk privacy information and limit the scope of privacy information dissemination, the blockchain-based proxy re-encryption access control method (BBPR-AC) is designed. Aiming at the problems of proxy re-encryption technology, such as the third-party agent being prone to evil, the authorization judgment being cumbersome, and the authorization process not automated, we design the proxy re-encryption access control mechanism based on the traceability of agricultural products' biological risk factors. Designing an attribute-based access control (ABAC) mechanism based on the traceability blockchain for agricultural products involves defining the attributes of each link in the agricultural supply chain, formulating policies, and evaluating and executing these policies, deployed in the blockchain system in the form of smart contracts. This approach achieves decentralization of authorization and automation of authority judgment. By analyzing the data characteristics within the agricultural product supply chain to avoid the malicious behavior of third-party agents, the decentralized blockchain system acts as a trusted third-party agent, and the proxy re-encryption is combined with symmetric encryption to improve the encryption efficiency. This ensures a efficient encryption process, making the system safe, transparent, and efficient. Finally, a prototype blockchain system for traceability of agricultural biological risk factors is built based on Hyperledger Fabric to verify this research method's reliability, security, and efficiency. The experimental results show that this research scheme's initial encryption, re-encryption, and decryption sessions exhibit lower computational overheads than traditional encryption methods. When the number of policies and the number of requests in the access control session is 100, the policy query latency is less than 400 ms, the request-response latency is slightly more than 360ms, and the data uploading throughput is 48.7 tx/s. The data query throughput is 81.8 tx/s, the system performance consumption is low and can meet the biological risk privacy protection needs of the agricultural supply chain. The BBPR-AC method proposed in this study provides ideas for achieving refined traceability management in the agricultural supply chain and promoting digital transformation in the agricultural industry. [ABSTRACT FROM AUTHOR]

Security of modern classical data encryption often relies on computationally hard problems, which can be trivialized with the advent of quantum computers. A potential remedy for this is quantum communication which takes advantage of the laws of quantum physics to provide secure exchange of information. Here, quantum key distribution (QKD) represents a powerful tool, allowing for unconditionally secure quantum communication between remote parties. At the same time, microwave quantum communication is set to play an important role in future quantum networks because of its natural frequency compatibility with superconducting quantum processors and modern near-distance communication standards. To this end, we present an experimental realization of a continuous-variable QKD protocol based on propagating displaced squeezed microwave states. We use superconducting parametric devices for generation and single-shot quadrature detection of these states. We demonstrate unconditional security in our experimental microwave QKD setting. The security performance is shown to be improved by adding finite trusted noise on the preparation side. Our results indicate feasibility of secure microwave quantum communication with the currently available technology in both open-air (up to ~ 80 m) and cryogenic (over 1000 m) conditions. Microwave-based quantum key distribution would allow a secure exchange of information in superconducting local area networks and, potentially beyond, in open-air conditions. Here, the authors provide a proof-of-principle implementation within a cryogenic environment, based on propagating displaced squeezed microwave states. [ABSTRACT FROM AUTHOR]

At present, social networks have become an indispensable medium in people's daily life and work. However, concerns about personal privacy leakage and identity information theft have also emerged. Therefore, a communication network system based on network slicing is constructed to strengthen the protection of communication network privacy. The chameleon hash algorithm is used to optimize attribute-based encryption and enhance the privacy protection of communication networks. On the basis of optimizing the combination of attribute encryption and homomorphic encryption,, a communication network privacy protection method using homomorphic encryption for network slicing and attribute is designed. The results show that the designed network energy consumption is low, the average energy consumption calculation is reduced by 8.69%, and the average energy consumption calculation is reduced by 14.3%. During data transmission, the throughput of the designed network can reach about 700 Mbps at each stage, which has a high efficiency.. The above results demonstrate that the designed communication network provides effective privacy protection. Encrypted data can be decrypted and tracked in the event of any security incident. This is to protect user privacy and provide strong technical support for communication network security. [ABSTRACT FROM AUTHOR]

Homomorphic encryption performs computations on encrypted data without decrypting, thereby eliminating security issues during the data communication between clouds and edges. As a result, there is a growing need for homomorphic encryption hardware (HE-HW) for the edges, where low power consumption and a compact form factor are desired. Here, a Pt/Ta2O5/Mo metallic cluster-type memristors (Mo-MCM) characterized by the Mo as a mobile species, and its utilization for the HE-HW via a 1-trasistor-1-memristor (1T1M) array as a prototype HE-HW is proposed. The Mo-MCM exhibits inherent stochastic set-switching behavior, which can be utilized for generating the random numbers required for encryption key generation. Furthermore, the device can accurately store analog conductance states after set-switching, which can be used as an analog non-volatile memristor. By simultaneously leveraging these two characteristics, encryption key generation, data encryption, and decryption are possible within a single device through an in-memory computing manner. Homomorphic encryption contributes to eliminating security issues during the data communication for edge computing. Here, the authors propose a 1-trasistor−1-memristor array as a homomorphic encryption hardware prototype. By leveraging the stochastic set-switching behavior and analog non-volatile properties of the memristor, the complete homomorphic communication process is demonstrated. [ABSTRACT FROM AUTHOR]

The secure transmission of medical images and related digital patient records on untrusted channels has recently become a focus in healthcare industries. Data hiding and encryption are important tools for this goal. This paper proposes a data-hiding method for medical images in the context of invisibility, robustness, security and low time cost. A dual watermarking is introduced to accomplish chaos-based encryption to ensure medical images' copyright protection and content security. First, a local binary pattern based on neighbouring pixels is used to compute an optimal value, called an embedding factor, for embedding both marks. Second, the host medical image is marked using the lifting wavelet transform, the lower–upper (LU) decomposition and singular value decomposition with an embedding factor to protect ownership. Last, the marked image is encrypted by using a 3D-chaotic map. The method is tested on two standard datasets, which is convenient for medical applications. Our experimental results and performance analysis demonstrate that the proposed scheme produces a peak signal-to-noise ratio (PSNR) and NC wat 1 / NC wat 2 of 54.82 dB and 0.9916/0.9928, respectively. Furthermore, the key space analysis of our encryption technique is greater than 2 100 , which provides a high protection degree against brute-force attacks. The proposed scheme achieves better robustness, imperceptibility, and security performance than previous schemes. Our method can reduce time costs by 98% (91% on average), which results in lower time costs than other conventional encryption techniques. [ABSTRACT FROM AUTHOR]

IoT devices produce a vast amount of data ranging from personal to sensitive information. Usually, these devices remain connected to the internet so protecting the information produced by them is crucial. Since most of the IoT devices are resource-constrained, they must be supported with lightweight encryption standards to protect information. Recent research has used the concept of context awareness to select the most suitable data encryption standard based on the device resources along with the required information confidentiality level. However, to effectively use the context information, it is required to be organized explicitly while considering the dynamic nature of IoT systems. In this regard, ontology-based systems effectively reduce the volume of manual work while recommending solutions. Currently, these systems cannot work with precision due to multiple uncertain factors of IoT sensory data. To overcome this challenge, this research proposes a fuzzy ontology-based context-aware system to protect IoT device information with the help of an encryption algorithm that considers device capabilities and user priorities regarding the data confidentiality. In order to automate the recommendation process, Semantic Web Rule Language (SWRL) rules and fuzzy logic are used, whereas, Description Logic and RDF Query Language is used to evaluate the results. The evaluation results confirm that the proposed method can produce results according to human perception by significantly increasing the accuracy of prediction. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency of cloud storage, deduplication technology has been widely used. In personal cloud storage, files are diverse. Diverse files contain files of different sizes and different popularity, some of which have many copies. Existing deduplication schemes mainly focus on data security but fail to improve the overall performance, including low computing overhead for diverse data. Using deterministic tags based on convergent encryption to identify data may leak data information, while using fully random tags generated by complex encryption algorithms may generate more computing overhead. To address the above issues, we proposed an encrypted deduplication scheme based on files diversity (FD-Dedup). Diverse files are identified by semi-random tags. We also designed a semi-random tag generation (SRTG) algorithm that coordinates the computing overhead and security. Security analysis and performance comparison show that FD-Dedup can balance security and computing overhead for diverse files in personal cloud storage. [ABSTRACT FROM AUTHOR]

Cloud computing technology offers flexible and expedient services that carry a variety of profits for both societies as well as individuals. De-duplication techniques were developed to minimize redundant data in the cloud storage. But, one of the main challenges of cloud storage is data deduplication with secure data storage.To overcome the issue, we propose Boneh Goh Nissim Bilinear Attribute-based Optimal Cache Oblivious (BGNBA-OCO) access control and secure de-duplication for data storage in cloud computing in this paper. The proposed method achieves fne-grained access control with low computation consumption. We design Boneh Goh Nissim Privacy Preserving Revocable Attribute-based Encryption that reinforces attribute revocation and averts the discharge of sensitive information. Furthermore, we utilize Optimal Cache Oblivious algorithm to prevent disclosure of access patterns to hide the access patterns in cloud storage via rand pattern matching. We support updating both encrypted data and access control policies to minimize communication and computation overhead of data duplication and encryption processes concurrently. We perform secure data sharing to achieve higher data confidentiality and integrity. Finally, we conducted the extensive experiments in cloud and the results illustrated that our proposed BGNBA-OCO method is more efficient than related works. [ABSTRACT FROM AUTHOR]

Photoluminescence (PL) colour-changing materials in response to photostimulus play an increasingly significant role in intelligent applications for their programmability. Nevertheless, current research mainly focuses on photochemical processes, with less attention to PL transformation through uniform aggregation mode adjustment. Here we show photochromic luminescence in organic crystals (e.g. dimethyl terephthalate) with PL varying from dark blue to purple, then to bright orange-red, and finally to red. This change is attributed to the emergence of clusters with red emission, which is barely achieved in single-benzene-based structures, thanks to the subtle molecular rearrangements prompted by light. Crucial to this process are the through-space electron interactions among molecules and moderate short contacts between ester groups. The irradiated crystals exhibit reversible PL transformation upon sufficient relaxation, showing promising applications in information storage and smart optoelectronic devices. This research contributes to the development of smart photochromic luminescent materials with significant PL colour transformations through molecular rearrangement. Color-changing emissions in organic crystals are often realized via photochemical reactions of their molecules. Here, the authors demonstrate reversible color change through more simple molecular rearrangements with application in encryption and data storage. [ABSTRACT FROM AUTHOR]

One of the routine exercises to manage and improve the performance and utility of the cloud is the migration or transfer of cloud data whether it is large or small. However, it is extremely challenging to protect both data privacy and integrity concurrently while moving cloud data, particularly when it is very vast. Collectively, prior works fail to offer a complete solution to these problem. Even though data encryption and steganography techniques are popular and efficient, they provide higher time and space complexities and introduce information loss. As a result, the goal of this research is to provide a chaos compression and encryption system based on chaos theory to guarantee both data privacy and integrity during the transit or migration of massive cloud data. During data transmission, the entire data are compressed using a chaotic substitution box followed by an adaptive Huffman encoding algorithms. Therefore, the input data are efficiently transformed into a non-readable form which replaces the original data, making it difficult for an unethical individual or group to determine its true sense. Our evaluation results show that the proposed chaotic technique has a maximum entropy value of 7.99, which supports its ability to provide more privacy when compared to previous techniques. It also delivers the best bits per code of 4.41, a throughput of 2.89 MB/s, and a minimal information loss percentage of 0.0011%, demonstrating its superior time, space efficiency, and ability to improve data integrity over existing methods. [ABSTRACT FROM AUTHOR]

Polymer-based pure organic room-temperature phosphorescent materials have tremendous advantages in applications owing to their low cost, vast resources, and easy processability. However, designing polymer-based room-temperature phosphorescent materials with large Stokes shifts as key requirements in biocompatibility and environmental-friendly performance is still challenging. By generating charge transfer states as the gangplank from singlet excited states to triplet states in doped organic molecules, we find a host molecule (pyrrolidone) that affords charge transfer with doped guest molecules, and excellent polymer-based organic room-temperature phosphorescent materials can be easily fabricated when polymerizing the host molecule. By adding polyaromatic hydrocarbon molecules as electron-donor in polyvinylpyrrolidone, efficient intersystem crossing and tunable phosphorescent from green to near-infrared can be achieved, with maximum phosphorescence wavelength and lifetime up to 757 nm and 3850 ms, respectively. These doped polyvinylpyrrolidone materials have good photoactivation properties, recyclability, advanced data encryption, and anti-counterfeiting. This reported design strategy paves the way for the design of polyvinylpyrrolidone-based room-temperature phosphorescent materials. Room temperature phosphorescent polymers have potential in a range of applications, but achieving the desired properties can be challenging. Here, the authors report the development of such polymer materials by doping with polyaromatic hydrocarbons. [ABSTRACT FROM AUTHOR]

Cryptography secures data and serves to ensure the confidentiality of records. Playfair is a cryptographic symmetrical algorithm that encrypts statistics based on key costs. This secret is shared with an authorized person to retrieve data. In the conventional pattern, there is an area complexity and deficiency in letters, numbers, and special characters. This hassle has been overcome in previous studies by editing pattern dimensions. The fillers used throughout the enciphering were not eliminated during the retrieval process, which resulted in the indiscrimination of the retrieved statistics. The proposed method uses a separate quadrate pattern that strengthens the Playfair cipher and guarantees that the fillers are eliminated to ensure the authentic retrieval of records. The fillers indiscriminate and strengthen the set of rules in opposition to brute force and avalanche impact. The proposed algorithm was evaluated with a minimal change in the key, and was found to have an avalanche effect between 65% and 93.7%. The encrypted document is further encoded using the Lempel–Ziv–Markov chain algorithm (LZMA) to provide compressed second-level secured text with a compression ratio of 0.75 for a file size of 100 KB. The pattern was designed to subsidize the integrated characters found on the keyboard. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the quantum circuit implementations of the lightweight authenticated encryption algorithm ASCON by using the NOT gates, CNOT gates, Toffoli gates, measurements, and the dynamic quantum circuits. Firstly, the quantum circuit of addition of constants is realized by adding the NOT gates according to the position of 1 in round constants. Secondly, the quantum circuit of S-box of the permutation is synthesized according to the classical circuit diagram of S-box. Then the linear layer functions are expressed in matrix form, and their quantum circuits are synthesized according to Gaussian elimination. Finally, we synthesize the whole quantum circuits according to the general diagrams of the authenticated encryption algorithm ASCON. The correctness of the quantum circuits of the S-box and the linear layer was verified by the Aer simulator of the IBM Quantum platform. As far as we know, this is the first implementation of the quantum circuits for the Authenticated Encryption with Associated Data (AEAD) of ASCON in-place. The maximum quantum resources for the three ASCON authenticated encryption algorithms were estimated. The quantum circuit of ASCON-128 uses a total of 320 qubits, 30,639 NOT gates, 128,814 CNOT gates, 8064 Toffoli gates, 10,752 measurements, and 5376 dynamic quantum circuits. The quantum circuit of ASCON-128a uses a total of 320 qubits, 23,558 NOT gates, 98,144 CNOT gates, 6144 Toffoli gates, 8192 measurements, and 4096 dynamic quantum circuits. The quantum circuit of ASCON-80pq uses a total of 320 qubits, 30,736 NOT gates, 128,814 CNOT gates, 8064 Toffoli gates, 10,752 measurements, and 5376 dynamic quantum circuits. [ABSTRACT FROM AUTHOR]

In recent years, the popularity of blockchain application in healthcare sector has increased manifold due to features such as decentralized architecture, security, immutability and authentication. However, there are some challenges associated with blockchain-based healthcare frameworks. Firstly, blockchain provides data verifiability meaning that anything stored there is accessible to all nodes in the network for verification. However, it is unacceptable for sensitive medical data to be made accessible to everyone. Secondly, healthcare sectors are group-oriented and frequently involve open networks for communication which lead to data breaches and other security risks. Lastly, due to limited size of a block in blockchain, many hospitals prefer storing patient's data locally in a centralized server or opt for cloud storage which have their own threat vectors. In this work, we propose a three-phase unified approach to solve the above problems. Our framework utilizes proxy re-encryption and advanced cryptographic techniques to provide stringent access control. Next, a blockchain-based group encryption is proposed to ensure secure group communication. A group session key will be agreed upon by the authorized group members and used to protect sensitive patient information. Lastly, IPFS-based blockchain data storage is proposed to maintain data securely offsite. We provide a comparative security analysis of the proposed framework with other existing peer models and show that our framework offers several new security features. We also examine the security of the proposed framework using BAN logic. Furthermore, the proposed framework is simulated using the OMNET++ software, and its storage and computation costs are examined to establish its effectiveness. [ABSTRACT FROM AUTHOR]

Cocrystal engineering is an efficient and simple strategy to construct functional materials, especially for the exploitation of novel and multifunctional materials. Herein, we report two kinds of nucleic-acid-base cocrystal systems that imitate the strong hydrogen bond interactions constructed in the form of complementary base pairing. The two cocrystals studied exhibit different colors of phosphorescence from their monomeric counterparts and show the feature of rare high-temperature phosphorescence. Mechanistic studies reveal that the strong hydrogen bond network stabilizes the triplet state and suppresses non-radiative transitions, resulting in phosphorescence even at 425 K. Moreover, the isolation effects of the hydrogen bond network regulate the interactions between the phosphor groups, realizing the manipulation from aggregation to single-molecule phosphorescence. Benefiting from the long-lived triplet state with a high quantum yield, the generation of reactive oxygen species by energy transfer is also available to utilize for some applications such as in photodynamic therapy and broad-spectrum microbicidal effects. In vitro experiments show that the cocrystals efficiently kill bacteria on a tooth surface and significantly help prevent dental caries. This work not only provides deep insight into the relationship of the structure-properties of cocrystal systems, but also facilitates the design of multifunctional cocrystal materials and enriches their potential applications. Cocrystal engineering is a promising strategy for constructing multifunctional materials. Here, the authors describe nucleic-acid-base cocrystal systems with different colors of phosphorescence from their monomeric counterparts and high-temperature phosphorescence with antimicrobial effects and data encryption applications. [ABSTRACT FROM AUTHOR]

The encryption of user data is crucial when employing electronic health record services to guarantee the security of the data stored on cloud servers. Attribute-based encryption (ABE) scheme is considered a powerful encryption technique that offers flexible and fine-grained access control capabilities. Further, the multi-user collaborative access ABE scheme additionally supports users to acquire access authorization through collaborative works. However, the existing multi-user collaborative access ABE schemes do not consider the different weights of collaboration users. Therefore, using these schemes for weighted multi-user collaborative access results in redundant attributes, which inevitably reduces the efficiency of the ABE scheme. This paper proposes a revocable and verifiable weighted attribute-based encryption with collaborative access scheme (RVWABE-CA), which can provide efficient weighted multi-user collaborative access, user revocation, and data integrity verification, as the fundamental cornerstone for establishing a robust framework to facilitate secure sharing of electronic health records in a public cloud environment. In detail, this scheme employs a novel weighted access tree to eliminate redundant attributes, utilizes encryption version information to control user revocation, and establishes Merkle Hash Tree for data integrity verification. We prove that our scheme is resistant against chosen plaintext attack. The experimental results demonstrate that our scheme has significant computational efficiency advantages compared to related works, without increasing storage or communication overhead. Therefore, the RVWABE-CA scheme can provide an efficient and flexible weighted collaborative access control and user revocation mechanism as well as data integrity verification for electronic health record systems. [ABSTRACT FROM AUTHOR]

Supply chain management has become increasingly complex, leading to information loss and delayed transmission, exacerbating the bullwhip effect. Furthermore, the need for more reliable information storage, traceability, and accountability has slowed supply chain management. In this context, blockchain technology (BCT) solves the bullwhip effect problem, as it supports distributed networking, information synchronization among nodes, digital encryption, traceable information, and unchangeable block content. This paper proposes using public blockchain to solve the bullwhip effect problem in the supply chain (SC), which has yet to be discussed in published academic research papers. To this end, a framework has been developed to determine the readiness of a supply chain for blockchain adoption. This framework includes a checklist to evaluate the motivation, timing, and appropriate platform for adopting blockchain. The framework has been validated using a case study of personal computer devices, which were affected by the Covid-19 pandemic and resulted in semiconductors supply chain disruption. The study involved polling four executives The study involved polling four executives (of large organizations in Egypt and some Middle Eastern countries) representing different stages in the supply chain, they are retail, distribution, manufacturing, and supply. The results showed that while the executives recognized the benefits of adopting blockchain, they were still determining if it was the right time for adoption and did not see the technology ready for their supply chains. Finally, some public blockchain platforms were introduced to help businesses choose the most suitable platform for adoption. [ABSTRACT FROM AUTHOR]

Encryption chips are specialized integrated circuits that incorporate encryption algorithms for data encryption and decryption, ensuring data confidentiality and security. In China, the domestic SM4 algorithm is commonly utilized, as opposed to the international AES encryption algorithm. These widely implemented encryption standards have been proven to be difficult to crack through crypt analysis methods Currently, power consumption side-channel attacks are the most prevalent method. They involve capturing power consumption data during the encryption process and subsequently recovering the encryption key from this data. The two leading methods are Differential Power Analysis (DPA) and machine learning techniques. DPA does not necessitate prior knowledge but relies heavily on the number of power consumption curves. With only 50 power consumption data points, the accuracy is a mere 80%. Machine learning methods require prior knowledge, achieving an accuracy rate above 95% with only 30 power traces, albeit with training times typically exceeding 15 min. In this paper, a distributed energy analysis attack approach was presented based on Correlation Power Analysis (CPA). The power consumption data was divided into 16 subsets, with each subset corresponding to 8 bytes of the key. By training each subset separately, the 8-byte key's corresponding power consumption data is reduced to only 100 dimensions, resulting in a 76% decrease in cracking time and a 3% improvement in cracking accuracy rate.This article also trains a more complex 256 classification model to directly crack the final key, achieving a success rate of 28% in cracking 128-bit passwords with only 1 power trace [ABSTRACT FROM AUTHOR]

The principal constituent of a block cipher in symmetric-key cryptography is the Boolean function, determining the substitution box (S-box). Block ciphers rely totally on S-boxes with excellent nonlinearity and upright cryptographic structures. In AES, an 8 × 8 S-box is a 16 × 16 lookup table over the Galois field GF 2 8 , that occupies 8 × 28 bytes storage of computer memory. By using traditional method to construct a 24 × 24 S-box over Galois field GF 2 24 , which lodges a storage memory of 24 × 224 bytes in traditional sense. Thus, the memory storage does not support a 24 × 24 S-box over a very larger order Galois field like GF 2 24 . A resolute of this difficulty is possibly coming out from the algebraic structure of the commutative finite chain ring F q [ x ] < x k > = ∑ i = 0 k - 1 x i F q. In this study, a subgroup of the multiplicative group of units of the chain ring F 2 [ x ] < x 24 > = ∑ i = 0 23 x i F 2 is considered to construct a 24 × 24 S-box that occupy just 24 × 28 bits storage memory of computer. The proposed S-box has a substantial potential to create confusion during substitution phase of the color image enciphering algorithm. While for the permutation component of the algorithm, DNA transform is applied for creating diffusion in the pixels of the color image. The proposed RGB image encryption attains the standard optimum level when compared it to the DNA and chaos-based image encryption techniques. [ABSTRACT FROM AUTHOR]

After the tremendous development and fast growth in communication systems and electronic devices, information security and preservation have become one of the most important procedures to be considered when transferring data between two parties. Encryption and data hiding are two of the most important techniques to protect the information sent over networks and the Internet. In this paper, a new technique of encryption and concealment is used through the following steps: First, the secret information is encrypted by using developed DNA to get (S1), second, by scrambling the encrypted data, the (S1) is diffused by using a zigzag method to get (S2), third, re-obfuscation the (S2) by using developed zigzag method through using Tinkerbell technique to get (S3), fourth, perform XoR operation between the (S3) and the Tinkerbell technique to get (S4), and fifth, the (S4) is hidden in the random locations of the cover image based on the LSB technique and the Tinkerbell technology, where the Tinkerbell has incredibly excellent characteristics and used to generate random sequence numbers twice with different initial and parameters value, once for the encryption process for scrambling secret information and once for the hiding process for determining hidden locations. Several metrics were used to evaluate the system's efficiency: histogram, PSNR, MSE, mean absolute error, bit error rate, encryption quality, Unified Average Changing Intensity, hamming distance, entropy, and correlation coefficient. The experimental results display that the suggested method has a good performance and reliability, high security, and greater embedding capacity and ensures higher image quality; also, the proposed method presented preferable outcomes when compared to other approaches. [ABSTRACT FROM AUTHOR]

Personalized medical data privacy and secure storage protection face serious challenges, especially in terms of data security and storage efficiency. Traditional encryption and storage solutions cannot meet the needs of modern medical data protection, which has led to an urgent need for new data protection strategies. Research personalized medical data privacy and secure storage protection based on hybrid encryption, in order to improve the security and efficiency of data storage. A hybrid encryption mechanism was proposed, which uses user attributes as keys for data encryption. The results show that the storage consumption of user attribute keys increases with the number of user attributes, but the consumption of hybrid encryption privacy storage technology is much smaller than that of traditional schemes. In the test, when the number of users increased to 30, the processing time first reached 1200 ms. During the increase in data volume, both test data and real data showed a brief decrease in attack frequency, but after the data volume reached 730–780, the attack frequency increased. It is worth noting that the performance of test data is better than that of real data. Personalized medical data privacy and secure storage protection based on hybrid encryption can not only effectively improve data security and reduce the risk of attack, but also greatly outperform traditional solutions in storage consumption and processing time. It has important practical significance for modern medical data storage protection. [ABSTRACT FROM AUTHOR]

Optical image/data encryption techniques are mostly based on the manipulation of spatial distributions of light's amplitude, phase, and polarization. Information encoding with phase involves complex interferometric set-up and polarization encoding requires Stoke's parameter measurement. Hence, they create difficulties in optical implementation. Considering the practical limitations, in this study, we demonstrate a method of single-shot intensity recording-based color image encryption by encoding the information in binary polarization states. The proposed method does not require Stoke parameter calculation. As a proof-of-concept, we demonstrated the technique with coherent and partially coherent light sources. Use of partially coherent light overcomes the speckle problem and makes the system cost-effective, useful for practical applications. [ABSTRACT FROM AUTHOR]

Quantum authentication is a fundamental first step that ensures secure quantum communication. Although various quantum authentication methods have been proposed recently, their implementation efficiency is limited. This paper proposes a key-controlled maximally mixed quantum state encryption (MMQSE) method using only a single qubit, unitary operation, minimized quantum transmissions, and a single qubit measurement, which improves implementation feasibility and operation efficiency. We applied it to representative quantum authentication applications, namely, quantum identity and message authentication. The security of our authentication schemes was verified by analyzing the relationship between the integral ratio of Uhlmann's fidelity and probability of successful eavesdropping. Moreover, we demonstrate the higher authentication efficiency of the proposed scheme in a real quantum-channel noise environment. The upper bound of the valid noise rate was quantified using the integral ratio of Uhlmann's fidelity in a noise environment. Finally, the optimal number of authentication sequences was estimated. [ABSTRACT FROM AUTHOR]

Image data is frequently processed in multimedia, wireless, mobile communication etc. The digital images transmitted over the internet are prone to security threats and thus providing security for the images and videos becomes an essential issue for individuals, business and governments. Moreover, applications in the automobile, banking, medical, construction and fashion industry require designs, scanned data, and blue-prints to be protected against attackers. Though many cryptographic algorithms are proposed in literatures, there is no much effort concentrated on the design of low-power hardware-efficient cryptosystem architectures. In this work, we propose a novel crypto architecture using multiple Boolean reversible blocks with logic control inputs derived from standard test images. The pre-processing and shuffling on the control pixel bits decide the depth of logic operation of the crypto system. The proposed design involves Gray Code Image Scrambling block for pre-processing, Reversible Shuffling Unit for bit plane modification and final merger for plane regrouping and is designated as Reversible Logic-Image Key (RL-IK) design. The use of reversible logic unit for shuffling combined with Gray code image scrambling in key generation improves the security of the processed images from the encryption unit at the expense of increase in area. To optimize the proposed RL-IK design in terms of area and security metrics, Gray Code bit plane processing is eliminated in the least n/2–1 bits as the contribution of least significant bits in the pixel intensity is less. The proposed Area and Security Optimized RL-IK Architecture (AS-RL-IK) involves same process as that of its standard counterpart in n/2 + 1 Most Significant Bits bits. As the weight based shuffling block is the critical unit of the proposed architecture that contributes for high delay and hardware area, for portable non-critical applications high speed hardware efficient variant of RL-IK is proposed. The proposed High Speed Area Efficient RL-IK (HSAE-RL-IK) design eliminates the weight based shuffling unit and employs only the multi-logic reversible block to produce the intermediate cipher image. The proposed crypto systems are designed using structural Verilog HDL. Simulations with 180 nm and 45 nm Application Specific Integrated Circuit technology reveals that RLC-IK design and its optimized variants exhibits 37% less power consumption and 35% less delay than Integer Wavelet Transform-Heterogeneous Key Generation (IWT-HKG) design with optimized security to the least when compared to the best of designs. [ABSTRACT FROM AUTHOR]

Alongside the rise of 'last-mile' delivery in contemporary urban logistics, drones have demonstrate commercial potential, given their outstanding triple-bottom-line performance. However, as a lithium-ion battery-powered device, drones' social and environmental merits can be overturned by battery recycling and disposal. To maintain economic performance, yet minimise environmental negatives, fleet sharing is widely applied in the transportation field, with the aim of creating synergies within industry and increasing overall fleet use. However, if a sharing platform's transparency is doubted, the sharing ability of the platform will be discounted. Known for its transparent and secure merits, blockchain technology provides new opportunities to improve existing sharing solutions. In particular, the decentralised structure and data encryption algorithm offered by blockchain allow every participant equal access to shared resources without undermining security issues. Therefore, this study explores the implementation of a blockchain-enabled fleet sharing solution to optimise drone operations, with consideration of battery wear and disposal effects. Unlike classical vehicle routing with fleet sharing problems, this research is more challenging, with multiple objectives (i.e., shortest path and fewest charging times), and considers different levels of sharing abilities. In this study, we propose a mixed-integer programming model to formulate the intended problem and solve the problem with a tailored branch-and-price algorithm. Through extensive experiments, the computational performance of our proposed solution is first articulated, and then the effectiveness of using blockchain to improve overall optimisation is reflected, and a series of critical influential factors with managerial significance are demonstrated. [ABSTRACT FROM AUTHOR]

Cloud computing has gained great attention among the individual user and the organization. Transitioning to the cloud platform is not simple as it involves various cybersecurity and operational issues. Due to a large amount of data storage in the cloud, ensuring the security of the data outsourced in the cloud is highly important. A Key Management System (KMS) is a secure data protection method that is commonly used in e-healthcare information systems, information security (confidentiality, integrity, authenticity), large-scale organizations, architecture security, sensor security, identity management, access control (privacy preservation), identity proofing (authentication), and legal issues. Because this approach allows the secret key information to be exchanged safely, the security level may be guaranteed to be high. Using a random prime number, a master secret key, and a parameter value, one can generate a secure key that is difficult for hackers to break. Secure data transfer with exact and consistent authentication is the goal of this new approach. This research focuses on the development of secure secret key creation and the improvement in secure key sharing. To generate the key (in the form of a QR code), we have used an asymmetric Elliptic Curve Cryptography (ECC) method, whereas encryption and decryption of data have been done by a hybrid of Advanced Encryption Standard (AES) and ECC cryptography. The hybrid ECC-AES model was found to take less amount of time than the AES model and other existing models. Current algorithms have certain security issues, such as vulnerability to plaintext attacks, brute force attacks, side-channel attacks, and computational complexity. The proposed algorithm has been able to overcome the issue of key exchange that plagues AES, simpler than ECC and more reliable than AES. As a result, KMS has been designed to provide high levels of security for healthcare information. We have proposed a Hybrid Cryptographic Approach to enhance the Mode of Key Management System (HCA-KMS) in a Cloud Environment based on authenticated encryption with AES and ECC. The proposed algorithm has been compared to existing methods concerning confidentiality, integrity, time complexity, storage overhead, resource utilization, security, and log time to demonstrate its efficacy. The proposed HCA-KMS has time complexity, encryption time (O (n)), and decryption time (O (logn)). [ABSTRACT FROM AUTHOR]

A physical unclonable function (PUF) is a foundation of anti-counterfeiting processes due to its inherent uniqueness. However, the self-limitation of conventional graphical/spectral PUFs in materials often makes it difficult to have both high code flexibility and high environmental stability in practice. In this study, we propose a universal, fractal-guided film annealing strategy to realize the random Au network-based PUFs that can be designed on demand in complexity, enabling the tags' intrinsic uniqueness and stability. A dynamic deep learning-based authentication system with an expandable database is built to identify and trace the PUFs, achieving an efficient and reliable authentication with 0% "false positives". Based on the roughening-enabled plasmonic network platform, Raman-based chemical encoding is conceptionally demonstrated, showing the potential for improvements in security. The configurable tags in mass production can serve as competitive PUF carriers for high-level anti-counterfeiting and data encryption. In order to be used on a large scale, unclonable tags for anti-counterfeiting should allow mass production at low cost, as well as fast and easy authentication. Here, the authors show how to use one-step annealing of gold films to quickly realize robust tags with high capacity, allowing fast deep-learning based authentication via smartphone readout. [ABSTRACT FROM AUTHOR]

The fabrication of chiral molecules into macroscopic systems has many valuable applications, especially in the fields of optical displays, data encryption, information storage, and so on. Here, we design and prepare a serious of supramolecular glasses (SGs) based on Zn-L-Histidine complexes, via an evaporation-induced self-assembly (EISA) strategy. Metal-ligand interactions between the zinc(II) ion and chiral L-Histidine endow the SGs with interesting circularly polarized afterglow (CPA). Multicolored CPA emissions from blue to red with dissymmetry factor as high as 9.5 × 10−3 and excited-state lifetime up to 356.7 ms are achieved under ambient conditions. Therefore, this work not only communicates the bulk SGs with wide-tunable afterglow and large circular polarization, but also provides an EISA method for the macroscopic self-assembly of chiral metal–organic hybrids toward photonic applications. Material designs with multicolor circularly polarized emissions are desirable for photonic applications. Here, the authors report supramolecular glasses based on self-assembled chiral metal–organic complexes with color-tunable circularly polarized afterglow. [ABSTRACT FROM AUTHOR]

Cloud-edge data security is a key issue in the internet of vehicles (IoV), as the potential for data breaches increases as more vehicles are connected. As vehicles become smarter and more connected, the risk of unauthorized access to the data generated by the vehicles also increases. Data encryption is a highly effective security measure that is widely used to protect the IoV from malicious actors. By encrypting data, it becomes virtually impossible for unauthorized individuals to access the information. This ensures that only the intended parties can access the data, allowing for secure communication between cloud and edge. Data encryption is a cost-effective and reliable security measure that is essential for any organization that relies on the IoV. The IoV is characterized by the large volume of data that is exchanged between devices in cloud and edge. This necessitates the use of a strong encryption method, such as stream ciphering, which is particularly well-suited to this type of environment. Stream ciphering provides the highest levels of security, making it the ideal choice for securing data transmission in the IoV. Many stream ciphering algorithms use bitwise exclusive or (XOR) to encrypt the data stream, so the core is the generation of a pseudo-random key stream. This paper proves that the probability of the number 1 appearing in the middle part of the Zeckendorf representation is constant, which can be used to generate pseudo-random key stream sequences. The pseudo-random sequence generated by the linear feedback shift register (LSFR) is periodic, and the key sequence will be duplicated. The logistic chaos (LC) sequence is too sensitive to the disturbance of initial value, and its stability is poor. In this paper, our proposed ZPKG (key generator based on Zeckendorf presentation) algorithm solves these two main problems in stream ciphering. The generated key sequence not only has strong randomness, but also is infinitely long, and it is robust to the minor disturbance of the initial value. [ABSTRACT FROM AUTHOR]

Long-term care refers to any support, both medical and non-medical, provided to the elderly with a chronic illness or disability due to physical or mental conditions. Since the cost of long-term care insurance is not inexpensive, low-cost devices and sensors can be used to create medical assistance systems to reduce human maintenance costs. The requirement of security and privacy under healthcare information protection is a critical issue for internet of medical things (IoMT) data transmission. In this paper, we designed an IoMT security robot for a long-term care system. The goal of this IoMT security robot is to provide secure transmission of the residents' private information. It is composed of three layers, namely, collection, encryption, and transmission. The function of the IoMT security robot is to first collect data from the patient or the elderly, then provide efficient data encryption, and deliver secured data transmission mechanisms to send the valuable data to the cloud. This IoMT security robot also has a server authentication mechanism, and a support IoT and IoMT devices inspection function. Our evaluation results showed that even when we utilized a low power consumption device like Raspberry Pi, AES algorithm achieved an encrypt and decrypt of 100–100 K bytes under 9 ms, which is a lot better than ECC, which takes about 104 ms. Further, we found that the AES only takes 0.00015 s to decrypt 100 Bytes data, which is way faster than the ECC algorithm, which takes 0.09 s. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) has a wide concentration in today's technological world. It has a significant impact on smart infrastructure with a security vision. So, IoT devices with sensors or smart gadgets are used to gather important data. The data gathered from IoT are vulnerable to signal processing attacks due to the interconnection of different network categories. In this paper, a system for securing data in IoT communication is proposed. The proposed system includes two techniques. Initially, a technique with the combination of Fuzzy and Particle swarm optimization (F-PSO) is utilized to determine a secure path. Then a cryptographic technique using the Learning with Errors over Rings (R-LWE) encryption scheme is adopted for data encryption. The trust value of every node in the network is calculated using trustworthiness analysis. Then based on the trust value, the malicious nodes are segregated. After that, the characteristics of secure nodes are utilized to find the secure path between source and destination. The secure path is selected optimally using F-PSO. After finding the secure path, the data are encrypted using the R-LWE technique. The proposed system attained a throughput of 96% with less than 0.1 ms delay. An enhanced trust-based secure routing and message delivery protocol attained better performance than existing such as Advanced Encryption Standard, Tiny Encryption Algorithm, eXtended TEA, and Rivest–Shamir–Adleman encryption schemes. [ABSTRACT FROM AUTHOR]

Deep learning accelerators have domain-specific architectures, this special memory hierarchy and working mode could bring about new crucial security vulnerabilities. Neural network reuse PE resources layer by layer, after a layer finished, accelerator will give an interrupt to inform host processor dispatch the next layer. By snooping on the interrupt signal patterns, we can capture specific deep neural network (DNN) models and launch hardware trojan attacks. In this paper, we propose Int-Monitor, a novel neural network model triggered hardware trojan in DNN accelerators. By implanting a well-designed interrupt monitor between the host processor and DNN accelerator, this backdoor can capture specific DNN models and trigger the trojan to attack DNN bias buffers. By attacking the global bias buffer, this trojan can prevent the activation of neurons in a DNN model. As result, the network forward propagation will be invalid and the accelerator will deny service. Runtime experiments on LeNet, Resnet, YOLOv2 and YOLOv4tiny DNN models show Int-Monitor can successfully attack the FPGA-based DNN accelerator SoCs. RTL synthesis and implementation show this trojan takes only small hardware overhead and negligible power consumption. It brings 0.5%, 0.2% hardware overhead and 0.622%, 0.187% power consumption on average in the SIMD and NVDLA accelerators. Unlike previous trojan using specially dedicated input data as a trigger, this novel trojan can enable hackers utilize DNN model as a trigger. This mechanism can make its escape from data pre-processing and data encryption. [ABSTRACT FROM AUTHOR]

Cloud computing plays a vital task in our daily lives, in which an enormous amount of data is stored daily on cloud storage. The highest priority for cloud data storage is guaranteeing the security of confidential data. The security of confidential data can be realised through utilising one of the cryptographic mechanisms including encryption and data hiding. With the rapid development for the realization of quantum computers, modern cryptosystems may be cracked including cloud systems. Accordingly, it is a crucial task for achieving confidentiality of data stored on cloud storage before the availability of quantum computers. Therefore, this study aims to utilise one of the quantum computational models, as a quantum-inspired system, to layout a new data confidentiality technique that can be applied in digital devices to have the capability for resisting the potential attacks from quantum and digital computers. In this paper, a new image security algorithm for real-time cloud applications using Gray code, quantum walks (QW), and Henon map is proposed. In the proposed image cryptosystem, the generated key streams from QW and Henon map is related to the plain image with high sensitivity of slight bit changes on the plain image. The outcomes based on deep analysis proves that the presented algorithm is efficient with high security for real-time application. [ABSTRACT FROM AUTHOR]

AES has been used in many applications to provide the data confidentiality. A new 32-bit reconfigurable and compact architecture for AES encryption and decryption is presented and implemented in non-BRAM FPG in this paper. It can be reconfigured for the options of different key sizes which is very flexible for the users to apply AES for various application environments. The proposed design employs a single-round architecture and subpipeling to minimize the hardware cost. The fully composite field GF((24)2)-based encryption/decryption and keyschedule lead to the lower hardware complexity and efficient subpipelining for 32-bit data path. In addition, a new subpipelined on-the-fly keyschedule over composite field GF((24)2) is proposed for all standard key sizes (128-, 192-, 256-bit) which generates the roundkeys simultaneously and efficiently. This feature is very useful and efficient when the main key has been changed since AES is a symmetric-key cryptography and the session key usually changes frequently. The proposed reconfigurable and compact design has higher throughput and lower hardware cost. It achieves throughputs of 375Mbits/s with 128-bit key, 318Mbits/s with 192-bit key and 275Mbits/s with 256-bit key on VIRTEX XC4VSX25-12, and the total number of slices is 1766. The proposed reconfigurable and compact AES architecture can be efficiently applied in computing-restricted environments such as wireless and embedded devices. [ABSTRACT FROM AUTHOR]

Traditional centralized cloud storage has difficulties in realizing the secure storage and sharing of speech and other multimedia data, as well as realizing fine-grained access control and privacy protection for speech data. To address this problem, we propose a distributed storage scheme for encryption speech data based on blockchain and inter planetary file system (IPFS). Our scheme is based on the characteristics of blockchain anti-tampering, decentralization and traceability. It is designed to ensure the security and controllability of private sensitive speech data of data users without the use of centralized cloud storage architecture. First, the ciphertext policy hierarchical attribute-based encryption (CP-HABE) scheme is used to encrypt the speech data. The encrypted speech data is then stored in the IPFS to achieve distributed storage. Second, a distributed and trusted access control policy is implemented by deploying an access control protocol Ethereum smart contract related to speech attributes. Finally, the proposed scheme is deployed and tested in the Linux environment, and the smart contract is deployed on the Ethereum test chain. Through experimental comparison with different storage schemes, analysis of the operational properties of our scheme and the evaluation of the quality index of the encryption scheme, the proposed scheme is shown to reliable, secure and scalable. [ABSTRACT FROM AUTHOR]

This study proposes a new encoding method, also known as an encryption chain based on the measurement result. Then, using the encryption chain to propose a unitary-operation-based semi-quantum key distribution protocol (SQKD) protocol. In the existing SQKD protocols, semi-quantum environments adopt a round-trip transmission strategy. In round-trip transmission, the classical participant must resend the received photons to the quantum participant after implementing local operations. Therefore, round-trip transmissions are vulnerable to Trojan horse attacks. Hence, the classical participant must be equipped with a photon number splitter and an optical wavelength filter device against Trojan horse attacks. This is illogical for semi-quantum environments because the burden on the classical participant is significantly increased as it involves the prevention of Trojan horse attacks. The proposed SQKD protocol is congenitally immune to Trojan horse attacks and involves no extra hardware because it is designed based on a one-way transmission as opposed to a round-trip transmission. When compared to the existing SQKD protocols, the proposed SQKD protocol provides the best qubit efficiency, and classical participants only require two quantum capabilities, which enhance its practicability. Moreover, the proposed SQKD protocol is free from collective attacks, Trojan horse attacks, and intercept-resend attacks. Thus, the proposed scheme is more efficient and practical than the existing SQKD protocols. [ABSTRACT FROM AUTHOR]

The rapid advancement of computation techniques and cloud computing has led to substantial advancements in Cyber-Physical Systems (CPS), particularly in the field of health care. There are a variety of ways in which CPS is used in healthcare today, including delivering intelligent feedback systems, automatically updating patient data digitally, monitoring patients passively with biosensors, etc. In recent years, cyber-physical systems have become capable of making lifesaving decisions as they are becoming more connected to the cloud. However, healthcare has become one of the most critical issues for many. A CPS network uses the Internet of Medical Things (IoMT) to continuously monitor patients' health metrics such as body temperature, heart rate, etc. Due to physical connectivity restrictions, networks are more susceptible to security threats. In spite of the fact that the data is stored in the cloud, it is necessary to provide security regardless of device security and network security. Several cyber-security vulnerabilities have been identified in cloud-based healthcare systems in particular. To give patients a reliable healthcare experience, security concerns with CPSs need to be addressed carefully. In this context, this paper proposes a Cross-Breed Blowfish and MD5 (CBM) approach to improve the security of health data in the CPS cloud. The proposed model uses the wireless sensor network, in which data acquired by the network is transmitted via the transmitting node. Using the fuzzified effective trust-based routing protocol (FET-RP), the most efficient path for data travel is selected. The best route is determined using Butter-Ant Optimization (BAO) algorithm. The proposed method conveys data throughput encryption and decryption in a decoded format. The encrypted data is then stored in the cloud database for security reasons. The route finding algorithm is the one which is sending the data from one end to other end. The data is encrypted based on the source and destination. We compare the performance metrics of our recommended technique to those of other existing techniques, such as RSA, Two fish, ICC, and FHEA, in order to ensure that it performs optimally. The values of Cross Breed Blowfish and MD5 and FET-RP with regard to the performance metrics in terms of encryption (60 ms), decryption (55 ms), latency (60 s), throughput (97 mbps), security level (98%), and execution time (57 ms) which outperforms the conventional methods by 10–15%. Also the proposed encryption shows the considerable improvement in the level of security making our model a real world solution. [ABSTRACT FROM AUTHOR]

This paper presents the findings of a systematic literature review aimed at elucidating the key anchors, strategies, methods, and techniques pertinent to trust management (TM) in cybersecurity. Drawing upon a meticulous analysis of 106 scholarly papers published between 2001 and 2024, the review offers a comprehensive overview of TM in cybersecurity practices in diverse cyber contexts. The study identifies seven foundational anchors crucial for effective TM frameworks: authentication, authorization, access control, privacy protection, monitoring and auditing, encryption and cryptography, risk management, and iterative and interactive trust processes. Additionally, ten overarching strategies emerge from the synthesis of literature, encompassing identity and access management, role-based access control, least privilege principle, digital certificates or public key infrastructure, security policies and procedures, encryption and data protection, continuous monitoring and risk assessment, vendor and third-party risk management, compliance management and continuous collaboration. Furthermore, the review delineates several methods instrumental in TM processes, and various techniques augmenting these methods were also identified, ranging from trust scoring algorithms and trust aggregation mechanisms to trust reasoning engines and trust-aware routing protocols. The synthesis of literature not only elucidates the multifaceted nature of TM in cybersecurity presented in a framework but also underscores the evolving strategies and technologies employed to establish and maintain trust in dynamic digital ecosystems. By providing a comprehensive overview of anchors, strategies, methods, and techniques in TM in cybersecurity. This review offers valuable insights for practitioners, researchers, and policymakers engaged in enhancing trustworthiness and resilience in contemporary cyber environments. [ABSTRACT FROM AUTHOR]

The resource-constrained nature of Internet of Things (IoT) devices and their diversity and abundancy represent a major challenge for the development of efficient security solutions that fit IoT systems and ensure end-to-end security. This paper presents an efficient IoT authentication scheme that provides mutual authentication between three different entities making up the IoT system under study; IoT devices, an IoT manufacturer server, and an authentication server. The authentication process is accomplished by the exchange of only six small messages in three successive stages: the IoT device association stage, the IoT device–AS server communication initialization stage, and the exchanged data encryption stage. The scheme employs the HMAC keyed hash function to provide mutual authentication and the AES-GCM lightweight symmetric cryptographic function to provide integrity and confidentiality for the exchanged data. The proposed scheme was simulated using the Network Simulator NS3 with C++ crypto++ library, using the various IoT enabling technology models. The obtained simulation results verified the proper functioning of the designed scheme and demonstrated the efficiency of the proposed scheme in terms of the low computational and communication overheads. The scheme needed 13.04 ms and 470 bytes to complete the mutual authentication process, including session key exchange. The low computational and communicational overhead of the proposed scheme are due to the scheme's small-sized messages, lightweight cryptographic functions, and passive discovery of IoT device. Security analysis of the scheme shows that the essential security requirements, which includes mutual authentication, confidentiality, and integrity, have been met by the proposed authentication scheme. Moreover, the scheme is inherently robust against common cyber-attacks such as the DoS, impersonation, spoofing, sniffing, and man-in-the-middle attacks. [ABSTRACT FROM AUTHOR]

In this study, we report a kind of fluorescence-structural color photonic crystals (FSC-PCs) based on ultraviolet (UV)-responsive core-interlayer-shell (CIS) colloidal particles. The preparation process includes the synthesis of UV-responsive CIS colloidal particles and quick fabrication of FSC-PCs patterns. Here, fluorescent precursor spiropyran was added to the semi-continuous emulsion polymerization system and grafted onto polymer chains to form the colloidal particles, which were quickly assembled by spray coating method into FSC-PCs within a few minutes. The FSC-PCs have long-range disorder arrangement and angle-independent structural colors, which show structural colors in visible light and red fluorescent color in 365 nm UV light. Therefore, we designed and fabricated a two-side security card, both sides of which show different information under different light conditions. During the light switching progress, completely different information can be demonstrated reversibly, allowing data encryption and reading. The FSC-PCs with a simple quick assembly process and unique optical properties have profound potential in anti-counterfeiting and data display. [ABSTRACT FROM AUTHOR]

Outsourcing data to the cloud can be considered as a perfect solution for the storage and computationally constrained data owners. However, data confidentiality is compromised when data are shared through the cloud. Cryptographic techniques like searchable encryption offer possible solutions of protect data from unauthorized access while facilitating searching without disclosure. Different searchable encryption techniques have been proposed; however, the techniques are limited in one way or the other, and none of them satisfies all the needs of confidentiality while sharing of data outsourced on the cloud. In this survey, we have identified the key performance indicators for confidentiality while sharing for cloud data along with possible attacks on searchable encryption techniques. A comprehensive study of the existing techniques searchable encryption on the anvil of the key performance indicators and robustness to attacks has been done. It was found that a technique may be suitable for an application with specific data confidentiality requirements, although no cryptographic silver bullet exists that satisfies all the performance metrics or is impervious to all the attacks. Moreover, most of the existing techniques are impracticable due to paradoxical requirements of data confidentiality and performance. A single mechanism may not suffice, and there is a need for a basket of efficient techniques that may provide accurate search with data confidentiality to make data sharing over the cloud an economically attractive option. [ABSTRACT FROM AUTHOR]

Attribute-based encryption(ABE) can enable user-centered data sharing in untrusted cloud scenario where users usually lack control on their outsourced data. However, existing ABE schemes have intrinsic limitations on scalability and revocation efficiency due to the bottleneck of a central authority and heavy re-encryption overhead on revocations. In this paper, we present a revocable decentralized attribute-based encryption scheme for data access control in cloud storage. In particular, by integrating decentralized attribute-based encryption, key regression technique, all-or-nothing transform, revocation list for involved attributes, and blacklist in a novel way, we provide a revocable ABE scheme with practical dynamic group membership and identity privacy protection, and meanwhile, it enhances the re-encryption efficiency caused by revocations without sacrificing security. We analyzed the security of our scheme. The experimental evaluation demonstrates that the cryptographic overhead on key derivation, encryption(decryption), and ABE ciphertext update are reasonable, and for the throughput of accessing encrypted data from the cloud, our scheme outperforms other schemes. [ABSTRACT FROM AUTHOR]

With the rapid development in world-wide technologies affecting large-scale applications, the Internet of Things (IoT) has gained a lot of attention from such applications. The Internet of Vehicles (IoV) technology is an exploration of the IoT where radio frequency identification (RFID), one of the promising technologies, can be employed in the IoV systems. However, security and privacy are a key concern in RFID-based IoV system. In the RFID systems during wireless communication among the tag and the reader, an adversary can perform malicious attacks and compromise data privacy. Apart from privacy and security issues, the computation capability and memory of the tags are very limited as compared to the backend server and the reader; therefore, an RFID-based authentication protocol suffers from the high computational overhead. To overcome these issues, we have put forward an anonymous and secure ultralightweight RFID protocol for Internet of Vehicles (AnonSURP). In order to reduce the overhead of the RFID tags, we have exploited the cross and the left rotate operations instead of a hash function for data encryption. In particular, the proposed protocol aims at ensuring the user's location privacy, data privacy, and resisting typical known attacks. Also, the proposed protocol is ensuring the low-cost of the RFID tags and providing fast certification speed. The informal analysis ensures that the protocol AnonSURP meets the various security requirements and provides resistance from various known attacks. Finally, a comparative analysis has been performed that demonstrates the better performance of the proposed protocol from the existing protocols. [ABSTRACT FROM AUTHOR]

CAVLC (Context-Adaptive Variable Length Coding) is a high-performance entropy method for video and image compression. It is the most commonly used entropy method in the video standard H.264. In recent years, several hardware accelerators for CAVLC have been designed. In contrast, high-performance software implementations of CAVLC (e.g., GPU-based) are scarce. A high-performance GPU-based implementation of CAVLC is desirable in several scenarios. On the one hand, it can be exploited as the entropy component in GPU-based H.264 encoders, which are a very suitable solution when GPU built-in H.264 hardware encoders lack certain necessary functionality, such as data encryption and information hiding. On the other hand, a GPU-based implementation of CAVLC can be reused in a wide variety of GPU-based compression systems for encoding images and videos in formats other than H.264, such as medical images. This is not possible with hardware implementations of CAVLC, as they are non-separable components of hardware H.264 encoders. In this paper, we present CAVLCU, an efficient implementation of CAVLC on GPU, which is based on four key ideas. First, we use only one kernel to avoid the long latency global memory accesses required to transmit intermediate results among different kernels, and the costly launches and terminations of additional kernels. Second, we apply an efficient synchronization mechanism for thread-blocks (In this paper, to prevent confusion, a block of pixels of a frame will be referred to as simply block and a GPU thread block as thread-block.) that process adjacent frame regions (in horizontal and vertical dimensions) to share results in global memory space. Third, we exploit fully the available global memory bandwidth by using vectorized loads to move directly the quantized transform coefficients to registers. Fourth, we use register tiling to implement the zigzag sorting, thus obtaining high instruction-level parallelism. An exhaustive experimental evaluation showed that our approach is between 2.5 × and 5.4 × faster than the only state-of-the-art GPU-based implementation of CAVLC. [ABSTRACT FROM AUTHOR]

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s13635-023-00150-3. [ABSTRACT FROM AUTHOR]

In the context of big data, the exploration of the application effect of machine learning in intelligent encryption for real-time image text digital information aims to improve the privacy information security of people. Aiming at the problem of digital information leakage of real-time image text, the convolutional neural network is introduced and improved by adding a preprocessing module to form AlexNet, to encrypt the digital information of real-time image text. Besides, to take into account both the security effect and the real-time performance of the system, the image text is encrypted by the chaotic sequence generated by a one-dimensional chaotic system called Logistic-Sine and a multi-dimensional chaotic system named Lorenz. In this way, a real-time image text encryption model is constructed by combining the chaotic function and AlexNet. Finally, a simulation experiment is performed to analyze the performance of this model. The comparative analysis indicates that the recognition accuracy of feature extraction of image text by the intelligent encryption model reaches 94.37%, which is at least 3.05% higher than that of other neural network models by scholars in related fields. In the security analysis of image text encryption, the information entropy of pixel values at (0, 0) of the proposed model is close to the ideal value 8. Meanwhile, the value of the number of pixels change rate is generally more than 99.50%, and the value of the unified average changing intensity is generally more than 33.50%. This demonstrates that the model has good security in resisting attacks. Therefore, the constructed model can provide good security guarantee under the premise of ensuring the recognition accuracy, which can provide experimental basis for improving the security performance of real-time image text data in the future. [ABSTRACT FROM AUTHOR]

With the rapid development of cloud computing technology and communication technology, cloud storage has become a tool used by people in daily life. Cloud storage service enables users to outsource data to cloud servers and retrieve desired document efficiently. Individual privacy in outsource data are very sensitive and should be prevented from any leakage. Public-key encryption with keyword search (PEKS) scheme resolves this tension, while public-key authentication encryption with keyword search (PAEKS) scheme improve its keyword guessing attacks problem potentially. Whereas, the loss of keyword privacy, the limitation of single user interaction and low efficiency make PEKS/PAEKS schemes far from enough in practical applications.In this paper, we develop a multi-recipient public key encryption scheme with keyword search without pairing (MREKS) for cloud storage under public key infrastructure. The proposed scheme has the merits of supporting multi-recipient keyword search way as well as requiring no expensively bilinear pairing operations under standard model. We present a concrete and efficient construction of MREKS, and prove its security based on discrete logarithm assumptions. Furthermore, we embed the algorithm of data plaintext encryption and decryption into the scheme, which makes the scheme more practical. We show that our scheme enjoys much more efficiency than previous PEKS/PAEKS scheme in the simulation experiment, especially the keyword encryption is optimized by 79.5%. [ABSTRACT FROM AUTHOR]

The purposes are to develop the patent data profoundly, control the data access process effectively, and protect the patent information and content. The traditional patent review systems are analyzed. For the present patent data security and privacy protection technologies and algorithms, the patent information data are stored on different block nodes after data fragmentation using blockchain technology. Then the data are shared using the data encryption algorism. In this way, data access control can be restricted to particular users. Finally, a patent data protection scheme based on privacy protection is proposed. The security of the scheme and the model performance are verified through simulation experiments. The time required to encrypt 10 MB files with 64-bit and 128-bit data is 35 ms and 105 ms, respectively. The proposed re-encryption algorithm only needs 1 s to decrypt 64 KB data, and only 1% of the data needs asymmetric encryption. This greatly reduces the computational overhead of encryption. Results demonstrate that the system can effectively control the access methods of users, efficiently protect the personal privacy and patent content of patent applicants, and reduce the patent office cloud computing overhead using the local resources of branches. The distributed storage methods can reduce the cloud system interaction of the patent office, thereby greatly improving the speed of encryption and ensuring data security. Compared with the state of the art methods, the proposed patent data access and protection system based on blockchain technology have greater advantages in data security and model performance. The research results can provide a research foundation and practical value for the protection and review systems of patent data. [ABSTRACT FROM AUTHOR]

Holography is a vital tool used in various applications from microscopy, solar energy, imaging, display to information encryption. Generation of a holographic image and reconstruction of object/hologram information from a holographic image using the current algorithms are time-consuming processes. Versatile, fast in the meantime, accurate methodologies are required to compute holograms performing color imaging at multiple observation planes and reconstruct object/sample information from a holographic image for widely accommodating optical holograms. Here, we focus on design of optical holograms for generation of holographic images at multiple observation planes and colors via a deep learning model, the CHoloNet. The CHoloNet produces optical holograms which show multitasking performance as multiplexing color holographic image planes by tuning holographic structures. Furthermore, our deep learning model retrieves an object/hologram information from an intensity holographic image without requiring phase and amplitude information from the intensity image. We show that reconstructed objects/holograms show excellent agreement with the ground-truth images. The CHoloNet does not need iteratively reconstruction of object/hologram information while conventional object/hologram recovery methods rely on multiple holographic images at various observation planes along with the iterative algorithms. We openly share the fast and efficient framework that we develop in order to contribute to the design and implementation of optical holograms, and we believe that the CHoloNet based object/hologram reconstruction and generation of holographic images will speed up wide-area implementation of optical holography in microscopy, data encryption, and communication technologies. [ABSTRACT FROM AUTHOR]

The deployment of virtual network functions (VNFs) at edge servers potentially impairs the performance of latency-sensitive applications due to their computational cost. This work considers a new approach to addressing this problem that provides line rate acceleration of VNFs by employing field-programmable gate array (FPGA) equipped edge servers. This approach has been validated by practical use cases with both TCP and UDP as underlying protocol on a physical testbed environment. We examine the performance implications of executing a security VNF at an FPGA-equipped edge server. We experimentally demonstrate reduced VNF execution latency and energy consumption for a real-time video streaming application in comparison with a software-only baseline. In particular, the results show that the approach lowers VNF execution latency and power consumption at the edge by up to 44% and 76%, respectively, in our experiments while satisfying time constraints and maintaining confidentiality with high scalability. We also highlight the potential research challenges to make this approach viable in practice. [ABSTRACT FROM AUTHOR]