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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]

With the number of attacks and cyberincidents affecting Internet of Things (IoT) devices on the rise, the need for carrying out forensic investigations to determine what has happened has grown at the same pace. However, due to the characteristics and requirements of this environment, the solutions used until now in the field are not suitable to be followed, as they are not able to guarantee the effective retrieval and study of the pieces of evidence. Under these circumstances, new ways of interacting with IoT units are needed, and the edge computing paradigm has emerged as an interesting asset to complement IoT networks. Attack, anomaly and intrusion detection, or data encryption are some of the fields in which this approach has been successfully applied. Following this concept, this article presents an IoT forensic methodology that integrates the edge computing technology in order to assist in the investigation process, trying to address some of the issues that are hindering the effectiveness of examinations in this scenario. In addition, this proposal is compared with the existing ones in the research community, and evaluated by testing it in two case studies representing real-life scenarios, ultimately demonstrating suitability to be used for IoT forensic examinations. [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]

In today's data-driven world, the exponential growth of digital information poses significant challenges in data management. In recent years, the adoption of cloud-based Electronic Health Records (EHR) sharing schemes has yielded numerous advantages like improved accessibility, availability, and enhanced interoperability. However, the centralized nature of cloud storage presents challenges in terms of information storage, privacy protection, and security. Despite several approaches that have been presented to ensure secure deduplication of similar EHRs, the validation of data integrity without a third-party auditor (TPA) remains a persistent task. Because involving a TPA raises concerns about the confidentiality and privacy of crucial healthcare information. To tackle this challenge, a novel cloud storage auditing technique is proposed that incorporates cross-patient block-level deduplication while upholding strong privacy protection, ensuring that EHR is not compromised. Here, we introduced blockchain technology to achieve integrity verification, thus eliminating the need for a TPA by providing a decentralized and transparent mechanism. Additionally, an index for all EHRs has been generated to facilitate block-level duplicate checks and employ a novel strategy to prevent adversaries from acquiring original information saved in the cloud storage. The security of the proposed approach is established against factorization attacks and decrypt exponent attacks. The performance evaluation demonstrates the superior efficiency of the proposed scheme in terms of file authenticator generation, challenge creation, and proof verification to other existing client-side deduplication approaches. [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]

Cryptography aims to design algorithms for the protection of important data transmitted over unsecured networks. These algorithms encrypt the data and render it incomprehensible even if it is captured by enemies. Today's data encryption standard is the AES algorithm. The most important and nonlinear unit in the AES algorithm is the s-box structure. The S-box provides the mixing process in the algorithm, that is, the confusion. An s-box structure with a high nonlinearity value greatly increases the security against various attacks. Therefore, s-box is of vital importance in an encryption algorithm. When we look at the literature, chaos-based s-box structures are frequently used. However, the nonlinearity value of s-boxes produced with chaos is low. In this article, a new, fast, and very simple method is proposed to increase the nonlinearity value of chaos-based s-box structures. In the proposed method, the nonlinearity value is calculated by changing the places of the elements respectively. When the nonlinearity value increases, the s-box is updated, and the next element is passed. In this way, many iterations are not looked at in vain. This saves a lot of time. As a result of the analysis, it has been proven that the s-box structure obtained by the proposed method is cryptographically strong and has a high nonlinearity value. It is thought that the proposed method will provide many advantages for future cryptography 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]

Quantum video encryption is an essential method for ensuring video content security. This paper proposes a quantum video encryption method based on bitplanes and improved Arnold scrambling. Firstly, we design a quantum video representation based on bitplanes (BRQV) and an improved Arnold scrambling to entangle video frames. Then, we use 2D quantum wavelet transforms and an improved logic mapping for frequency-domain encryption. The encryption security analysis reveals that the post-encryption SSIM value is close to 0.015, with an information entropy reaching 7.9541. The circuit complexity analysis shows that the proposed method can realize the video encryption using 16 n 3 + 272 n 2 - 88 n quantum basic gates with the circuit width 2 n + log 2 n + 5 . The best existing quantum video encryption method needs O (2 n n 3) quantum basic gates with the circuit width 3 n + 3 . Simulation results demonstrate that the proposed video encryption method exhibits low correlation coefficients and high efficiency. [ABSTRACT FROM AUTHOR]

Data privacy is becoming more important as the internet of things (IoT) rapidly expands. There are significant consequences for the broad adoption of the internet of things. Homomorphic encryption is one possible solution for protecting sensitive data in the IoT. However, there is a great deal of potential for efficiency gains. In order to get enough privacy and security, it is also crucial. Our homomorphic encryption technique for secure and private optical fibre communication is detailed in this publication. The data owner, fog server, and data consumers' privacy is the primary focus of the proposed architectural design. The performance of this research shows that our FCHE solution improves data security throughout the data storage operation and reduces encryption length. This research also aims to analyse the factors of optical fiber communication cost, storage cost, and computing cost in the context of FCHE. [ABSTRACT FROM AUTHOR]

The rapid development of network technology makes the implementation of ubiquitous tasks possible in which the Flying Ad-Hoc Network(FANET) plays an important role. Control stations distributed in different task areas can control UAVs in FANET to complete a complex task. However, the application of FANET brings about problems of identity security and data security. Attackers can impersonate legal entities to issue fake commands or modify task data, which will hinder the smooth execution of tasks. The existing centralized entity authorization method has the single point of failure problem, and the distributed method based on the blockchain does not consider the entity security and data security issues at the task level. Therefore, to protect the entity identity security and task data security of ubiquitous tasks in FANET, in this paper, we propose a blockchain-based ubiquitous entity authorization and management scheme (BUAMH), which uses smart contracts and homomorphic encryption technology to achieve entity registration, access control and dynamic task member management. Specifically, the blockchain is used to record and protect entity behavior information and the results of smart contracts. Five smart contracts are designed to realize the authorization and management of entity identity. Besides, Homomorphic encryption technology is used to manage UAVs while protecting entity privacy. Furthermore, a side-chain structure is constructed and an identity consensus mechanism(ICM) is proposed to manage multi tasks and speed up the consensus of miners, respectively. The experimental results show that the computational costs and communication costs of the proposed BUAMH are superior to the existing technology. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) applications are revolutionizing lifestyles and social management. In IoT environments, there is a need to deploy a large number of sensing devices, which are typically resource-constrained, with limited computational power and communication resources. Due to its open nature, IoT applications confront potential security and privacy risks in exchange for convenience, with data privacy being a significant concern. Predicate encryption (PE) offers a promising approach to address this concern. However, most PE schemes are public-key cryptosystems, which are more expensive compared to symmetric cryptography. These costs are burdensome for resource-constrained devices, especially when dealing with massive amounts of data. A recent study by Viet et al. (ESORICS'2022) introduced a symmetric PE scheme. However, this scheme's representation of attributes and predicates is limited. To overcome this limitation, we propose a flexible symmetric PE scheme. In the proposed scheme, predicates and attributes are represented using vectors. Tokens are related to predicates, while ciphertexts are associated with attributes. The encrypted message can be decrypted when the values of the predicate vector and attribute vector are pairwise unequal. This scheme enables fine-grained access control over encrypted data, ensuring that users with any attribute value in the vector embedded in the ciphertext cannot decrypt it. The security analysis demonstrates that the proposed scheme effectively protects data privacy. Additionally, performance evaluations indicate that the scheme is efficient, providing a lightweight solution for data privacy in IoT environments. [ABSTRACT FROM AUTHOR]

Cloud computing (CC) is a rapidly growing technology that is deployed by various organizations due to the high level of scalability, elasticity, and virtualization it offers. However, security-related challenges arise due to insecure access control points. Security models in the cloud such as authentication, data recovery, confidentiality, accessibility, and data integrity. This includes the deployment model, barriers in cloud computing, cloud services, and security issues. Data security can be improved via the usage of encryption and decryption keys during transmission. However, the existing techniques often suffered from improved time consumption and complexity in handling more users. This paper mainly focuses on the data security issue with the outsourced sensitive data in the cloud server by designing a novel Modified Multi-scale Convolutional Neural Network-based Zebra Optimization (MMCNN-ZO) approach to improve the cloud data sharing system. The proposed MMCNN-ZO approach safeguards the crucial data effectively and outputs in the form of cipher text/image. Here, the weight functions of the MMCNN are tuned mechanically using the ZO algorithm for the enhanced encryption process. The decryption process is performed to obtain the data in user understandable format. These procedures make the proposed system effectively secure the data content by protecting against intrusions. The efficacy of the proposed MMCNN-ZO method is investigated using diverse evaluation indicators namely throughput, decryption, and encryption time. The proposed MMCNN-ZO algorithm achieved improvements in terms of throughput, encryption time, and decryption time of 7450 bits/sec, 4.82 ms, and 4.86 ms respectively compared to other existing methods of SVM, ANN, BPPSVC, and GBCRP. The experimental results inherit the better performances of the suggested MMCNN-ZO approach over other methods in terms of all metrics. [ABSTRACT FROM AUTHOR]

Data hiding along with the security plays a vital role in the wireless network. In recent years, object detection, Feature Extraction (FE) and correlation based technique are developed to predict the pixels that is suitable for embedding. However, traditional data hiding method still suffered in the selection of less distortion pixels. To overcome these shortcomings, this method proposes (i) Moving Object (MO) detection, (ii) FE, (iii) data hiding, and (iv) data encryption. Initially, the MO in the video are detected using optical flow and tracking the weight of MO. Next, data hiding features are extracted using Optimization Fruit fly Algorithm (OFA) with Differential Evolution (DE) and Opposition Based Learning (OBL) algorithm. Then, a modified data hiding techniques based on correlation, regression and pixel segmentation with Prediction Error (PE) techniques are used for improving the performance. Finally, the hidden data is encrypted using Binary Tree Structure (BTS) to provide additional layer of security. Experimental result shows the proposed method is superior to other state-of-the-art methods in terms of Peak-Signal-to-Noise Ratio (PSNR), embedding capacity and security analysis. [ABSTRACT FROM AUTHOR]

The industrial internet of things (IIoT) refers to a system of interconnected equipment, sensors, and devices deployed within industrial environments whose primary function is to collect and facilitate the exchange of data. IIoT has gained significant traction in several domains, encompassing remote monitoring, equipment management, and condition tracking. The utilization of IIoT in different environments gives rise to apprehensions regarding the security of data. As a result of this, it is imperative to ensure that rigorous safety measures are in place to safeguard the confidentiality of the sensitive information being transmitted. The utilization of elliptic curve cryptography (ECC) and quantum key exchange (QKE) in IIoT networks holds promise for achieving robust and predictable security measures. ECC is a widely adopted type of public-key cryptography due to its efficiency and security. It has gained significant popularity in contemporary systems. QKE is an innovative methodology that originates from the fundamental principles of quantum physics. The system has the ability to generate a secret key that is impervious to hacking attempts, as it leverages natural principles instead of conventional mathematical procedures. Due to this characteristic, quantum key distribution (QKD) is widely recognized as one of the most reliable methods for key exchange. The combination has led to the creation of a novel cryptographic model that integrates elliptic curve cryptography (ECC) and quantum key exchange (QKE) techniques for the generation and distribution of cryptographic keys. The model leads to an increase in the base probability of the Bennett–Brassard protocol (BB84) from 0.5 to 1. Subsequently, the keys that are produced are employed for the encryption of data through a streamlined and adapted variant of the Advanced Encryption Standard (AES), thereby expediting the secure exchange of data while upholding its level of safeguarding. [ABSTRACT FROM AUTHOR]

This paper presents an image encryption scheme with data and appearance security, by adopting inter-intra-block scrambling and weighted diffusion. The 2D robust hyper-chaotic map with flexible geometric distribution and rich hyper-chaotic parameter space is employed to generate the key stream for encryption, by considering the characteristics of plaintext. The plain image is first preprocessed by Huffman coding for getting compressed image. Then, the compressed image is divided into four sub-blocks and is further permuted by the designed inter-intra-block scrambling scheme, which can improve the scrambling effect by making the pixel far away from the original adjacent pixels. After that, a weighted diffusion method strongly related to plaintext and key stream is introduced to diffuse the shuffled image to obtain the noise-like cipher image. And in pursuit of higher security, the meaningless noise-like image is embedded into host image to create the visually meaningful cipher image. A series of experiment tests and analyses are carried out to further demonstrate the excellent performances of the encryption scheme. [ABSTRACT FROM AUTHOR]

With the advancement of content-based medical image retrieval (CBMIR) technology which is used as a convenient assistant for medical diagnosis. However, the potential risk of privacy disclosure in CBMIR remains a concern due to the involvement of patients' sensitive information in medical images. To address this issue, we have proposed an efficient scheme to achieve privacy-preserving medical image retrieval, named PMIR. The primary objective of PMIR is to enhance the accuracy of medical image retrieval while ensuring privacy protection. In PMIR, medical institutions with large repositories of medical images can securely upload to the cloud server with their image data and encryption indexes. Subsequently, users who successfully registered from medical institutions are able to enjoy convenient image retrieval services without revealing their sensitive information and query attributes to the cloud server. The proposed approach emphasizes a privacy-preserving policy mechanism, which empowers users with the right to choose rather than relying solely on service providers. Through rigorous security analysis, it is demonstrated that PMIR can effectively withstand various known security threats. Additionally, experimental results highlight the substantial reduction in communication overhead achieved by PMIR, ultimately providing a seamless and secure search experience for users. [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]

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]

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]

Cloud storage is the ideal solution for outsourcing big data since the cloud can store a large amount of data. Cloud storage, on the other hand, raises additional problems about data duplication, fine-grained access control, and privacy, all of these factors are crucial for cloud large data storage. Data duplication approaches based on encrypted data schemes now available do not provide for fine-grained access control. This paper proposes a secure framework for managing data using rapid asymmetric maximum based dynamic size chunking and fuzzy logic for deduplication. Chunking, fingerprinting, hashing, and writing are the four main process of the proposed method. Initially, chunking is done to split the files into chunks. Rapid Asymmetric Maximum (RAM) based Dynamic Size Chunking (DSC) is used in the proposed method. These chunked files are then fingerprinted using hashing process for ensuring data authentication. Then B-tree indexing approach is used in the proposed method in order to keep the fingerprinted in an organized state. General Type2-Fuzzy logic is using Ant Lion Optimization (ALO) is used for detecting duplicate files in the documents. In the cloud storage platform, only non-duplicate documents are safely kept. The Triple Data Encryption Standard is used to do a security study before outsourcing non-duplicate data to a third-party cloud server. The total computation time of the proposed technique is 0.4 s in the inline phase and 0.04 s in the offline phase, and the deduplication ratio is 95% in the inline phase and 90% in the offline phase. This proposed deduplication approach requires less storage, which reduces memory use and processing time. [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]

Electronic payment (E-payment) systems rely heavily on secure communication, typically achieved through encryption processes in cryptography. Traditional cryptography often relies on complex mathematical problems for encryption, such as difficult decompositions or extracting discrete logarithms. With the development of quantum computing, the security of these classical encryption methods is under threat. To address this challenge, quantum E-payment protocols have emerged as a potential solution. However, the practical quantum E-payment protocols are limited due to the channel transmission efficiency decreasing exponentially with distance. This is further constrained by the Pirandola–Laurenza–Ottaviani–Banchi (PLOB) bound. To address this challenge, we propose a twin-field quantum encryption protocol for E-payment based on blockchain. In our protocol, we propose a twin-field quantum encryption method to authenticate identity and detect eavesdropping simultaneously. It not only eliminates side-channel attacks on the detectors but also has the potential to break the PLOB bound. Our security analysis shows that our E-payment protocol exhibits security properties such as blindness, unforgeability, and undeniability. Furthermore, our protocol demonstrates withstand against common inside and outside attacks. [ABSTRACT FROM AUTHOR]

Cloud computing (CC) is an emerging field in the IT sector due to its prospective, progress and incredible impact on the development of that sector. CC is a centralized and distributed network comprised of interrelated and interconnected systems, and the whole universe uses the cloud for the ultimate portion of data transmission. However, the cloud cannot provide security assurance, which is one of the main drawbacks of the cloud. Blockchain is the fascinating massive attention in the cloud field because of its security features. It consists of a chain of several blocks composed of multiple transactions. These data available in blocks are encrypted and cannot be altered by any in the world. Several emerging applications are affected by insurance companies, anomalies, thieves, and intruders fetching individual data and disturbing the user's routine. This paper develops a blockchain-based modified infinite chaotic elliptic cryptography (MICEC) to improve and tighten the security in the cloud. It contains three stages: protection of authentication, ownership protection, and identity mapping validation. At first, MICEC is employed for an authentication process that combines the infinite elliptic curve cryptography and modified chaotic neural network for pair of key generation and data encryption. In addition, the hash function is generated with the aid of the improved message digest 5 algorithm. Second, the improved Message Content Recommendation Algorithm with Latent Dirichlet Allocation is used to compute the score values. At last, cosine similarity matching criteria is computed in the validation based on the digests. The proposed work is simulated using the JAVA programming language with NetBeans IDE. The performance is evaluated and compared to other methods. [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]

In recent days, cloud computing is a universal computing and conventional paradigm, in which the resources are provided over the Internet based on requirements. With the huge growth of cloud storage and processing, security in Cloud has become the most captivating research domains. Though there are many methods for enhancing security and data confidentiality over cloud, security is the major threat among data owners and users in data storages and data sharing between two parties in Cloud. In data sharing, for assuring security, the data are secured with key and the key is required to be encrypted to keep that not accessible for attacks. With that concern, this work develops a Quantum Cryptography based Cloud Security Model (QC-CSM) that uses Quantum Key Distribution Protocol (QKDP) for sharing the secret key between parties. For ensuring the data owner about the security of their share data over Cloud, Attribute Based Encryption (ABE) is used. Further, the data can be accessed by an authenticated user, who is having the access for decryption through the key from a secure quantum channel. The results show that the proposed model outperforms the existing works by providing a more secure environment and confidential data sharing between entities in minimal time in the Cloud framework. [ABSTRACT FROM AUTHOR]

In conjunction with pandemics, medical image data are growing exponentially. In some countries, hospitals collect biometric data from patients, such as fingerprints, iris, or faces. This data can be used for things like identity verification and security management. However, this medical data can be easily compromised by hackers. In order to prevent illegal tampering with medical images and invasion of privacy, a new texture fusion medical image encryption (TFMIE) algorithm derived from biometric images is proposed, which can encrypt the image using biometric information for storage or transmission. First, the medical image is decomposed into n-bit-planes by bit-plane decomposition. Secondly, a fusion image is generated by a biometric image with a circular local binary pattern and pixel-weighted average method. The fused image is further decomposed into n bit-planes through bit-plane decomposition and performs XOR operation with the original medical image in reverse order. Following the execution of the XOR operation, a new scrambling and diffusion algorithm based on a one-dimensional fractional trigonometric function (1DFTF) chaotic map is employed to form the cipher image. The experimental results show that compared with the existing methods, the average information entropy value of TFMIE is 7.99, and the average values of NPCR and UACI reach 0.9958 and 0.3346, respectively, which have strong key sensitivity, good robustness, and anti-attack ability. The method is lossless and has high transmission efficiency, which can meet the needs of medical big data encryption. [ABSTRACT FROM AUTHOR]

The limitation of traditional comparison protocols lies in the plaintext transmission of data or the sharing of encryption keys, which may lead to the risk of privacy disclosure. Compared with traditional comparison protocols, quantum private comparison (QPC) protocols utilize the characteristics of quantum computing and communication to provide higher security and privacy protection. Users in different domains often cannot communicate directly or find it difficult to choose the same trusted third party. Previous QPC protocols often had the same trusted or semi-honest third party and were unable to cope with private data comparison in cross-domain environments. We use product states of three-particle GHZ state and four-particle cluster state to realize QPC in cross-domain environment, and users only need to select the nodes they trust in their own domain. Then, we analyze the security of the protocol under various attacks, and show the security under channel node collusion attacks. Finally, we compare this protocol with other protocols to show that our protocol can be adapted to cross-domain environments. [ABSTRACT FROM AUTHOR]

In this paper, a comprehensive analysis of traveling wave solutions of two nonlinear Schrödinger type equations are carried out with help of three different integration techniques namely the tanh–coth, Kudryashov and sine–cosine methods. These equations include the (2 + 1)-dimensional perturbed nonlinear Schrödinger's equation and cubic–quintic nonlinear Schrödinger's equation. The obtained travelling wave solutions are in the form of rational function solutions, trigonometric function solutions, exponential function solutions and hyperbolic function solutions. Our proposed results showed that these techniques are reliable to study the nonlinear PDEs in fiber optics. The higher order cubic–quintic nonlinear Schrödinger equation (NLSE) explains the transmission of incredibly low signals and broadband communications that stretch into the spectral region, as well as the doping of optical fiber and the encryption of data in optical fibers. [ABSTRACT FROM AUTHOR]

Green edge computing aims to reasonably allocate computing resources on the premise of ensuring the reliability of information services. The computing power gap between terminal and edge server makes the traditional encryption algorithm waste too much energy when dealing with massive redundant data. How to improve encryption efficiency and reduce the computing consumption of massive data terminal equipment on the premise of ensuring data security is one of the goals of green edge computing. We proposed a data compression and encryption scheme based on compression sensing, which greatly reduces the computing consumption of computing limited data terminals; At the same time, the hyper chaotic system is used to further encrypt the data by Arnold transform, bitwise XOR and data random scrambling. In order to solve the problem that compressed sensing can not accurately recover data, we designed a nonlinear encryption scheme based on Chinese Remainder Theorem as a supplement. The simulation results show that the proposed data compression and encryption method is effective and reliable, which has high security performance, compression ability for text data and images, and high recovery ability when the compression ratio is more than 0.5. [ABSTRACT FROM AUTHOR]

E-health solutions for smart cities seem quite promising in resolving health problems, however, there are many challenges associated with it and one of the challenge is the secure and reliable error-free transmission/reception of medical images and associated data. In this paper, we have proposed an efficient technique to securely as well as reliably transfer medical images. In our proposed technique, we use singular value decomposition (SVD) and Discrete Wavelet Haar Transformation (DWT) for hiding the data while encryption is done through standard cipher key. At the receiving end, SVD, DWT, and the key are used to decrypt the image and extract both the image and hidden data. Extensive simulations are carried out on MATLAB in order to evaluate various parameters such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Bit Error Rate (BER) and robustness test, in order to illustrate the robustness and imperceptibility of the proposed technique. Our simulation results have proven the suitability of our algorithm for data hiding in medical images. [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]

As tweakable block ciphers from public permutations, tweakable Even–Mansour ciphers are widely used in disk sector encryption and data storage encryption. With the rapid improvement of computing power, especially the development of quantum computing technology and quantum computers, the quantum security of tweakable Even–Mansour ciphers should be concerned and studied. This paper focuses on the security of tweakable Even–Mansour ciphers in the quantum setting. For one-round tweakable Even–Mansour cipher, we give its quantum circuit, present a quantum key recovery attack in polynomial time by Simon's algorithm and show the concrete resource estimation. For two-round tweakable Even–Mansour cipher, we present a better quantum key recovery attack by BHT-meets-Simon algorithm than that by Grover-meets-Simon algorithm from a new perspective of variable tweaks and show the concrete resource estimation. Finally, we generalize to r-round tweakable Even–Mansour cipher and present a quantum key recovery attack by combining Grover's algorithm and Simon's algorithm. Our work is of great importance. We use BHT-meets-Simon algorithm to achieve better quantum key recovery attacks than Grover-meets-Simon algorithm for the first time. [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]

Telehealth and cloud-based communication platforms now hide medical data. Text and multimedia data are hidden using encryption, steganography, and watermarking. Steganography may hide medical data in images, music, video, text, and more. Using optical lights, optical steganography deciphers concealed messages. This study established an effective optical steganography model for telemedical data security. Polynomial Cryptographic LSB Substitution (PCLSB-S) reduces the distortion and increases medical data imperceptibility by using two-level randomised cryptographic technique with polynomial variable estimation. Advanced encryption standard and polynomial variables for video cover increase data security in which the medical text, picture, and audio payload capacity increased with PCLSB-S model. PCLSB-S model boosts payload and resilience, according to experiments. PCLSN-S model worked for optical steganography. [ABSTRACT FROM AUTHOR]

This research suggests a unique ECG security solution based on the data pattern-based encryption paradigm to address security issues in ECG signal transmission or storage environments. According to this concept, the encryption system controls the data security process by extracting key signatures from the ECG signal peaks to identify the characteristics or attributes of the data and encrypt it. To estimate the hashing qualities, the approach is to build a random key pattern based on the signal peaks and extract the signature. The signal was then encrypted and sent to a doctor or signal analyzer. Bilateral random hashing (BRH) is used to achieve this. This updates the hashing generation model by analyzing the parameters using probabilistic distributional characteristics. This crucial motif was applied. This key pattern was utilized to encrypt the data samples using the downhill peak follow (DPF) encryption technique, which follows the strength of the peak value in the ECG waveform. This suggested project is carried out using MATLAB scripting. [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]

The growth of media services, multimedia conferencing, interactive distance learning, and distributed interactive simulations is becoming more dependent on the security of multicast communication over 5 G and 6 G networks. In order to ensure the security and efficacy of multicast communication, our research came up with the idea of combining multicast public-key encryption with digital signatures known as "Multi-Receiver Signcryption (MRSC)." As compared to multicast encryption and signature primitives, MRSC significantly improves the effectiveness of secure information delivery through multicast communication over 5 G and 6 G networks. In this paper, we first provide the formal model of MRSC schemes used in Public Key Infrastructure, Identity-based Cryptography, and Certificateless Cryptography. Secondly, we present a typology of MRSC, as well as a summary of an in-depth investigation of the qualities of security, the cost of computing, and the overhead of communication over the networks. [ABSTRACT FROM AUTHOR]

With the development of information technology, the high-speed private data stream encryption transmission system is more and more widely used in the field of education. The high-speed private data stream encryption transmission system can realize high-speed and safe data transmission and protect the privacy and security of user data. To protect the security of private data in the online education of specialty "traffic engineering", an encryption transmission system for high-speed private data stream is designed. After the online education system and core modules of traffic engineering are analyzed, the system framework is designed through the codec module and the high-speed privacy data stream processing control and transmission module. The sliding window segmentation method is used to extract the privacy data in the education system and send it to the coding sub-module. Based on a homomorphic encryption algorithm, a private data stream encryption and decryption model is established. The key encoding is designed by the vector quantization coding method. The private data is authenticated according to the characteristics of the key, and the data encryption transmission is completed through the microcontroller. The experimental results show that the encrypted data of the designed system has only 0.01 Gbit loss, and the encryption time is only 93ms. The data dimension displayed after encryption is relatively scattered, and the distribution probability of encrypted data is between 1500–2000, which can effectively encrypt the private data in the online education system of transportation engineering specialty, and improve the security of high-speed private data flow in the online education system of transportation engineering specialty. [ABSTRACT FROM AUTHOR]

Electronics-Health Care is one of the new ideas in the healthcare industry. For analyzing the patient's records, doctors need a centralized record of the patients, which gives useful and enormous information. There will be a threat of leaking of confidential e-health data, which will seriously endanger by modifying the health care data of medical and its individual entities. Protection of the confidential data of patients will be a primary constraint in the health care industry. There is a lot of progressiveness in the human services area as well as there is a lot of usage of the information gathered from various sensors and this information is stored in the cloud. As per the existing security algorithms, there is still some security breach and also it won't get satisfied with integrity and consistency while transferring the data from one vendor to others in the health care system. It also causes high spoofing of IP and side channel hackers. With the increase in the use of the internet, there is an increase in hacking also, especially in the health-care sector, e-commerce, military, and Education. Dealing with the huge volume of information in the electronics-healthcare area requires the processing of patient's information day by day and its memory allocation. Cloud is the best option to store these health records in a distributed manner rather than on a single server. So, whatever the information gathered from it will be encoded on block chain technology and an anonymous digital ring signature will be used to authorize the intended user and maintain the privacy of patient cloud-based data distributed Electronics health record system before sending the information to the cloud storage. In this paper, the protection of Personal data of the patient health data is enhanced with block chain and anonymous ring signatures in the e-healthcare cloud; thus making it suitable for real-time applications. [ABSTRACT FROM AUTHOR]

With the advent of the Internet of Things (IoT), security methods need improvisation to prevent data stealing. Since IoT transfers the various heterogeneous data such as video, text, data signals, and even voices, efficient security systems must overcome the various attacks in the networks. IoT is often connected with low power devices, and these devices are vulnerable to attacks as it contains low security. Therefore, this requires a robust encryption method to protect the user data from the attacker. Traditional methods such as Data Encryption Systems (DES) and Advanced Encryption Systems (AES) are playing an essential role in ensuring the security in IoT devices, and the presence of substitution boxes (S-boxes) makes the system even more complex to counterfeit the attacks mainly side-channel attacks. Researchers claim that these traditional S-boxes need to be improvised when transmitting heterogeneous data, especially the images over the network. In this paper, A Novel dynamic substitution boxes are designed based on hybrid logistic-Henon maps with the deoxyribonucleic acid (DNA) coding systems to improve the security level of images against the side-channel attacks. The proposed structure uses the three-dimensional hybrid chaotic maps to increase the key space and uses the DNA pattern of operations to endure more security. The extensive experimentations are carried out for the proposed scheme and compared with the existing AES S-box structures. Analysis shows that the proposed structure is more resistant against side-channel attacks, as alleged. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) and smart medical devices have improved the healthcare systems by enabling remote monitoring and screening of the patients' health conditions anywhere and anytime. Due to an unexpected and huge increasing in number of patients during coronavirus (novel COVID-19) pandemic, it is considerably indispensable to monitor patients' health condition continuously before any serious disorder or infection occur. According to transferring the huge volume of produced sensitive health data of patients who do not want their private medical information to be revealed, dealing with security issues of IoT data as a major concern and a challenging problem has remained yet. Encountering this challenge, in this paper, a remote health monitoring model that applies a lightweight block encryption method for provisioning security for health and medical data in cloud-based IoT environment is presented. In this model, the patients' health statuses are determined via predicting critical situations through data mining methods for analyzing their biological data sensed by smart medical IoT devices in which a lightweight secure block encryption technique is used to ensure the patients' sensitive data become protected. Lightweight block encryption methods have a crucial effective influence on this sort of systems due to the restricted resources in IoT platforms. Experimental outcomes show that K-star classification method achieves the best results among RF, MLP, SVM, and J48 classifiers, with accuracy of 95%, precision of 94.5%, recall of 93.5%, and f-score of 93.99%. Therefore, regarding the attained outcomes, the suggested model is successful in achieving an effective remote health monitoring model assisted by secure IoT data in cloud-based IoT platforms. [ABSTRACT FROM AUTHOR]

Smartphones have become small computers that meet many of our needs, from e-mail and banking transactions to communication and social media use. In line with these attractive functions, the use of smartphones has greatly increased over the years. One of the most important features of these mobile devices is that they offer users many mobile applications that they can install. However, hacker attacks and the spread of malware have also increased. Today, current mobile malware detection and defense technologies are still inadequate. Mobile security is not only directly related to the operating system and used device but also related with communication over the internet, data encryption, data summarization, and users' privacy awareness. The main aim and contribution of this study are to collect the current state of mobile security and highlight the future of mobile security in light of the recent mobile security threat reports. The studies in the field of malware, attack types, and security vulnerabilities concerning the usage of smartphones were analyzed. The malware detection techniques were analyzed into two categories: signature-based and machine learning (behavior detection)-based techniques. Additionally, the current threats and prevention methods were described. Finally, a future direction is highlighted in the light of the current mobile security reports. [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]

In recent times, many innovative techniques are enabled in the real-time business environment and becoming more popular day by day in the cloud platform. The IT platform is expecting a whole new level of development by implementing new innovative technologies to a greater extent without employing additional infrastructure. Security is a critical concern in a shared environment in the current era, and it remains unresolved in the cloud. Data replication is also challenging to sustain performance, including data availability, reliability, scalability, bandwidth, access latency, and storage capacity constraints. Hence, data must be replicated to different nodes to achieve greater performance in the shared environment. Once the data is placed on to the backend storage, no proper encryption method is implemented when data is in motion and rest. This research proposes a new method to secure a one-time password in a two-factor authentication mechanism. The research employs, proves, and ensures strong security. The second method proposed in this research is to place the optimal number of replicas on different nodes to offer high availability. The replication using the packing coloring process is performed over multiple servers and optimizes the replica, which leads a path to space efficiency. The final method is a graph-based data encryption strategy that performs encryption on data in backend Redundant Array of Independent Disk (RAID) storage using crypto keys generated by the packing coloring process. The dynamic keystream considered in the proposed research offers better security. This research offers a novel architecture that proves strong security, improved authentication, and optimal replica placement with minimal cost. [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]

Hadoop is one of the biggest software structures for distributing the data to compute and handle big data. Big data is a group of composite and enormous datasets that contains a massive amount of data such as real-time data, social media, capabilities of data management, money laundering, and so on. Also, big data is measured as regards terabytes and petabytes. The main issue of the Hadoop application is unauthorized access. There are several existing techniques introduced to secure the data, but they have data errors, malicious attacks, and take a long time to compute. So the author proposed a novel ChaApache framework to secure the Hadoop application from an unauthorized person also to save processing time of data, and reduce the error rate. The main aim of the developed replica is securing data from an unauthorized person or unauthorized access. Moreover, the developed ChaApache framework is implemented in python, and the Hadoop application contains 512 bits of data, and the data are encrypted by four 32 bits. Furthermore, the proposed model is compared with other existing replicas in terms of computation time, resource usage, data sharing rate, encryption speed, and so on. [ABSTRACT FROM AUTHOR]

This paper gives a novel and efficient steganography technique based on hybrid algorithms that improves the various important parameters like PSNR, MSE, IF, capacity, security. It increases the security of the confidential data by using the encryption method and give improved quality of stego images with less error rate. This paper utilizes a grouping of wavelet domain & Salp Swarm based Optimization Algorithm (SSOA) and proposed embedding process for increasing the payload capacity. Initially, the integer discrete wavelet transform is utilized to process the cover image and DWT to extract the hidden image accurately. Furthermore, an edge localization process is proposed to localize the edge region of detail bands efficiently, which can be done by SSO Algorithm. To enhance the quality of the stego pictures, a deep enhanced stacked auto encoder (DESAE) has been proposed. The evaluation result of this technique achieves good image quality and high security. Also, it increases the payload capacity of the existing methods, which confirms the superiority of the proposed method compared to previous related techniques. [ABSTRACT FROM AUTHOR]

With the enormous amount of data growing exponentially, data owners aim to share data with each other to acquire an enhanced analytic view of their data. Distributed association rule mining over cloud computation helps data owners to extract knowledge from multiple databases. However, privacy is an important concept for data owners who want to share data and extract knowledge from aggregated data. This study proposes an outsourcing method to securely share and mine association rules from multiple parties protecting all parties' privacy. In this research, we utilize the properties of homomorphic encryption and propose a custom secure communication protocol. In our study, privacy of the shared data of all parties is ensured and we will not perform decryption in any step of the proposed method. We show that previous schemes could not properly guarantee the integrity of messages, furthermore, we propose our innovative communication protocol that uses an integrity checking function based on homomorphic encryption to authorize each party's shared data. We have implemented our scheme and showed even though an additional communication burden exists in our method, this method outperforms its competitors in terms of elapsed time and security. We have achieved more security especially in confidentiality and integrity of messages due to use of our proposed secure communication protocol. We also measured our proposed method's precision of mining parameters with different datasets to show the accuracy of our method on different scales will not change. [ABSTRACT FROM AUTHOR]