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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]

The article concentrates on exploring the issue of privacy‐preserving sliding mode consensus of multi‐agent systems (MASs) with disturbance. An encryption and decryption algorithm has been proposed to address data security and privacy issues during data transmission. To optimize network resource allocation, a dynamic event‐triggering mechanism has been introduced, which reduces the number of encrypted data while saving the computation cost. The consensus performance based on the sliding mode control strategy is achieved when the reachability of the slide‐mode surface is guaranteed, and then the slide‐mode controller is developed. Finally, an empirical demonstration through a numerical example validates the efficacy of the proposed strategy. [ABSTRACT FROM AUTHOR]

Summary: Communicating large amounts of data requires an encryption solution that ensures fast and secure data transfer. Unfortunately, it faced privacy and security issues, resulting in higher power consumption, data scarcity, energy, diversity, data reliability, low security, and packet loss in the communication process. The goal of this research is to ensure data transfer while conserving energy and protecting data transmission in WSNs. Therefore, this paper proposes a multipath routing protocol using the HGSPSO algorithm, which is a combination of hybrid gravitational search algorithm (HGSA) and particle swarm optimization (PSO), to securely transmit data from one node to another node under public and private key cryptography. The PSO approach is utilized to resolve the energy hole problem by selecting the cluster head in the sink coverage area. The RSA can be employed for data encryption, data decryption, key generation, and sharing. The metrics like acceleration constants and inertial weights are used for the HGSPSO algorithm. The result of this implementation demonstrated that the scheme had a low energy consumption of 36%, a maximum packet delivery ratio (PDR) of 96%, a higher throughput rate of 88%, and a low packet loss of 39%. [ABSTRACT FROM AUTHOR]

To date, a diverse array of smart materials, drawing inspiration from nature, is developed, exhibiting remarkable shape or color‐changing capabilities, which hold great promise in applications such as bionic soft robots and information encryption platforms. Achieving reversible shape‐shifting and color variation harmoniously within a single material is a particularly appealing prospect. Herein, a facile approach to creating such materials is presented, capable of undergoing reversible shape and color‐change synchronously. This is achieved by harnessing the stress‐free two‐way shape‐memory effect (2W‐SME) of a liquid crystal elastomer (LCE), meticulously programmed at both macro and micro scales. Specifically, the LCE with stress‐free 2W‐SME is fabricated, and permanent grating nanostructures are meticulously constructed through UV‐assisted nanoimprinting. By enabling reversible shape alterations at multiple dimensions, encompassing both macro and micro scales, the LCE material concurrently exhibits reversible changes in shape and color, triggered by heat. As a result, intelligent information encryption and decryption platforms that leverage the unique capabilities of LCE are demonstrated. The outcomes of this research endeavor are poised to pave the way for the advancement of smart materials in the realms of data storage and encryption. [ABSTRACT FROM AUTHOR]

In this work, we have used the standard symmetric key block cipher data encryption algorithm RC5(32,16,8) for the encryption of digital greyscale images. For this, we have only considered the nonzero elements of the sparse matrix of the images which have been generated using the sparse representation technique. The security strength of the proposed technique is verified through different quality parameters, e.g. information entropy, correlation coefficients, NPCR, UACI, and NIST test. Our proposed algorithm achieved the maximum information entropy value of 7.9977 for the cameraman image and nearly zero correlation coefficient values establish the robustness of the cryptosystem. The highest NPCR and UACI values obtained in our work are 99.6916 and 33.9605, which are closer to the maximum theoretical values. The proposed technique is also compared with some of the contemporary works to validate the credibility of our proposed algorithm. [ABSTRACT FROM AUTHOR]

An essential security component for the Internet of Things (IoT) is device authentication. IoT devices are widely dispersed in public and open areas, making them vulnerable to attacks. To detect the security violations, an authentication with a privacy preservation model is developed in this research using devised Autoregressive Poor and Rich Optimization (APRO)-based secret key. Here, the secret key used to perform the encryption process is generated by the proposed optimization algorithm in such a way that the data encryption mechanism is carried out by considering the Box-Cox transformation. However, the authentication process is achieved between the server and the Authorization center (AC) through the generation of authentication and verification messages. The original data is retrieved back by employing the decryption process along with the usage of the retrieval key. The proposed method achieved a minimum computation time of 0.062 sec, higher encryption quality of 92.56%, and minimum memory usage of 2.86MB. [ABSTRACT FROM AUTHOR]

With the rapid development of the information age, smart meters play an important role in the smart grid. However, there are more and more attacks on smart meters, which mainly focus on the identity authentication of smart meters and the security protection of electricity consumption data. In this paper, an efficient lightweight smart meter authentication scheme is proposed based on the Chinese Remainder Theorem (CRT), which can realize the revocation of a single smart meter user by publishing a secret random value bound to the smart meter identity. The proposed scheme not only protects the security of smart meter electricity consumption data by using encryption, but also resists identity attacks from both internal and external adversaries by using hash functions and timestamps. Experiment shows that the proposed scheme has lower computation overhead and communication overhead than other authentication schemes and is more suitable for smart meter authentication. [ABSTRACT FROM AUTHOR]

Improving the photoswitching rate and robustness of photochromic molecules in bulk solids is paramount for practical applications but remains an on‐going challenge. Here, we introduce an octupolar design paradigm to develop a new family of visible light organic photoswitches, namely multi‐branched octupolar Stenhouse Adducts (MOPSAs) featuring a C3‐symmetrical A3‐(D‐core) architecture with a dipolar donor–acceptor (D–A) photochrome in each branch. Our design couples multi‐dimensional geometric and electronic effects of MOPSAs to enable robust ultrafast reversible photoswitching in bulk polymers. Specifically, the optimal MOPSA (4 wt %) in commercial polyurethane films accomplishes nearly 100 % discoloration in 6 s under visible light with ∼ 100 % thermal‐recovery in 17.4 s at 60 °C, while the acquired kinetics constants are 3∼7 times that of dipolar DASA counterpart and 1∼2 orders of magnitude higher than those of reported DASAs in polymers. Importantly, the MOPSA‐doped polymer films sustain 500 discoloration/recovery cycles with slow degradation, superior to the existing DASAs in polymers (≤30 cycles). We discover that multi‐dipolar coupling in MOPSA enables enhanced polarization and electron delocalization, promoting the rate‐determining thermal cyclization, while the branched and non‐planar geometry of MOPSA induces large free volume to facilitate the isomerization. This design can be extended to develop spiropyran or azobenzene‐based ultrafast photochromic films. The superior photoswitching performance of MOPSAs together with their high‐yield and scalable synthesis and facile film processing inspires us to explore their versatile uses as smart inks or labels for time‐temperature indicators, optical logic encryption and multi‐levelled data encryption. [ABSTRACT FROM AUTHOR]

MOTIVATION: With the enhancement of people's awareness of the protection of personal privacy information, how to provide better services on the premise of protecting users' privacy has become an urgent problem to be solved. Therefore, it is a necessary motivation to build a network intelligent platform for privacy protection and integrated big data mining. OBJECTIVE: In view of the existing network platform of data privacy leakage, low efficiency of data mining and user satisfaction is not high, this paper will adopt advanced privacy technology, to ensure the confidentiality of users' personal information and security, to enhance the user trust and use experience, to better meet the needs of users. METHODS: In order to better protect the privacy of users, the network intelligent platform should adopt more advanced privacy protection technology. This paper uses the differential privacy algorithm to reduce the risk of data leakage and abuse, and ensure the accuracy and efficiency of data analysis and mining. In the design of the platform, the performance of the platform is fully taken into account to realize the secure storage and efficient processing of data, with good scalability and flexibility to meet the growing user needs and business needs. The performance of the network intelligent platform is also analyzed by experimental simulation. RESULT: The experimental results of this article indicated that in a network intelligent platform based on privacy protection and integrated big data mining, its data transmission encryption score was 9.5; the data storage encryption score was 9.8; the score of access control mechanism was 9.3; the privacy protection score was 9.6; the response time was 80 ms; the processing speed was 121GB/h; the user satisfaction rating was 6.6. CONCLUSION: This indicated that the network intelligent platform had good platform performance and user friendliness while ensuring data security and privacy protection. It could efficiently conduct data mining and ensure data security and privacy. [ABSTRACT FROM AUTHOR]

Symmetric cryptography provides the best examples of cryptosystems to be applied in lightweight environments (e.g., IoT). A representative example is the cryptosystem TinyJambu, one of the ten finalists in the NIST Lightweight Cryptography Standardization Project. It is an authentication encryption with associated data scheme that is extremely lightweight and fast. In this work, we analyze the security of TinyJambu from two distinct and non-symmetric points of view: (1) the improvement of the best cryptanalytical attack found in the literature and (2) a randomness analysis of the generated sequences. Concerning item (1), we launched a differential forgery attack with probability 2−65.9487, which was improved considerably compared with previous numerical results. Concerning item (2), we analyzed the degree of randomness of the TinyJambu keystream sequences with a complete and powerful battery of statistical tests. This non-symmetric study shows the weakness of TinyJambu against cryptanalytic attacks as well as the strength of TinyJambu against statistical analysis. [ABSTRACT FROM AUTHOR]

This paper introduces a methodology for generating secure cryptographic key bits from analog values obtained from the Lorenz chaotic circuit. The analog values are transferred from the chaotic circuit to the computer via an Analog Discovery-2 device and then post-processed by using a fixed-point number representation format and Von-Neumann corrector for the sampled values on the MATLAB program. By employing this method, the analog values are digitized and randomized as the main idea is to obtain secure and efficient statistically random bits. Furthermore, the generated random bits are utilized for secure audio encryption by demonstrating a practical application of the proposed methodology. In addition to the classical randomness test criteria, NIST 800.22 statistical test suite, the throughput bit stream is also subjected to Chi-square and FIPS 140-1 tests to further evaluate its effectiveness. The results of these comprehensive tests confirm the successful performance of the proposed system in generating statistically random bits and its secure audio encryption system. The utilization of the Lorenz chaotic circuit as an entropy source in generating true random bits for secure audio transmission applications showcases the potential of the proposed system. [ABSTRACT FROM AUTHOR]

To hide confidential messages from people who are not responsible or who can access the messages, a way is needed to hide the messages. One way to hide messages in transmission is to change the data into something unintelligible by encoding and embedding it using cryptography and steganography techniques. This application was built using the hill cipher algorithm and the Rivest Cipher 4 (RC4) method. This algorithm is a symmetric key algorithm which has several advantages in data encryption. The hill chiper algorithm uses a mxm matrix as the encryption and decryption key. Meanwhile, the RC4 symmetric key is in the form of a stream cipher which can process input data as well as messages or information. Input data is generally in the form of bytes or even bits. The results of this research show that hill cipher and RC4 have their respective advantages and disadvantages. However, currently, RC4 is generally considered less safe for use in securitycritical scenarios due to its vulnerability to attack. It is highly recommended to use an encryption algorithm such as advanced encryption standard (AES) which is modern and strong and has been tested and proven to be more resilient. [ABSTRACT FROM AUTHOR]

The efficiency of tools used to collect private medical data on people has significantly improved over time. These include implanted, surfacemounted, or encircling devices that form a wireless body area network (WBAN). Although the most recent secure authentication techniques in the industry offer privacy and security, these schemes have a higher time cost for authentication and take longer to complete owing to the restricted computational power of WBAN devices. We provide a novel authentication method depending on the lightweight wearable device scheme for the WBAN environment. Wearable devices are used to capture sensor data from the patient's body in the beginning, after which any redundant data is removed by normalization. The method we suggest for encrypting the data is multi-fractional triphase duplex data encryption (MTDDE) with ant colony optimization (ACO). The method considers not only the security of the data but also the many limitations of sensor nodes, such as battery life, throughput, computing power limitations, and dynamic topology. The thorough research demonstrates that our suggested technique saves computing costs while maintaining security and privacy together with anonymous verification. The suggested system's effectiveness in protecting the privacy and confidentiality of patient health data in WBAN is demonstrated by the simulation model. [ABSTRACT FROM AUTHOR]

To secure sensitive medical records in the healthcare clouds, this paper proposes an End-to-End Encryption (E2EE) to enhance a patient-centric blockchain-based system for electronic health record (EHR) management. The suggested system with a focus on the patient enables individuals to oversee their medical records within various involved parties by authorizing or withdrawing permission for access to their records. Utilizing the inter-planetary file system (IPFS) for record storage is chosen due to its decentralized nature and its ability to guarantee the unchangeability of records. Then an E2EE enhancement maintains the medical data integrity using dual level-Hybrid encryption: symmetric Advanced Encryption Standard (AES) and asymmetric Elliptic Curve Cryptography (ECC) cryptographic techniques. The proposed system is implemented using the Ethereum blockchain system for EHR data sharing and integration utilizing a web-based interface for the patient and all users to initiate the EHR sharing transactions over the IPFS cloud. The proposed system performance is evaluated in a working system prototype. For different file sizes between 512 KB to 100 MB, the performance metrics used to evaluate the proposed system were the time consumed for generating key, encryption, and decryption. The results demonstrate the proposed system's superiority over other cutting-edge systems and its practical ability to share secure health data in cloud environments. [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]

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function, a brand-new tristable locally active memristor model is first proposed in this paper. Here, a novel four-dimensional fractional-order memristive cellular neural network (FO-MCNN) model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its performance. Then, its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation platforms. Subsequently, it is used toward secure communication application scenarios. Taking it as the pseudo-random number generator (PRNG), a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing (ASR-CS) model. Eventually, the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance. [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]

In the age of big data, information security has become more and more essential for the Internet of Things. Since the software encryption algorithm can be easily hacked, the hardware security system has emerged as a reliable way to safeguard information. Here, a GaOx-based memristor array is experimentally demonstrated, which features a good multi-level storage capacity, 20 ns switching speed, and highly linear conductance modulation of over 500 states by multi pulses. An artificial neural network and an XOR circuit were further constructed based on this memristor array. This work connects memristor array-based handwritten digit recognition and data security circuit, forming a new data security management system for secure password input and transmission. [ABSTRACT FROM AUTHOR]

The object of research is the method and algorithm of arithmetic addition of binomial numbers generated by binary binomial counting systems. The lack of binomial arithmetic, in particular the operation of adding binary binomial numbers, in a certain way prevents their introduction into information systems and the construction of information and communication technologies based on them for combinatorial optimization, generation of combinatorial objects, data compression and encryption. In the framework of the proposed approach, instead of operating with binomial coefficients, only operations with their upper and lower parameters are carried out. At the same time, the weighting coefficients of binary binomial numbers, which are added to each other, are represented in the form of two-component tuples. Taking this into account, this paper presents an algorithm for binomial arithmetic addition using dynamic arrays. The main idea, which is included in the structure of the algorithm of binomial arithmetic addition based on dynamic arrays, is that the transition from a two-dimensional model of summation to a one-dimensional one is carried out. At the same time, only available, existing binomial coefficients are placed in the dynamic array. Accordingly, the search for binomial coefficients equal to or greater than the quantitative equivalent takes place in much smaller areas. In comparison with the algorithm based on matrix models, this quite significantly reduces the amount of time spent when performing the summation operation, and also reduces the requirements for the amount of memory required for placing two-component tuples of the assembly array. In the course of the research, a several-fold decrease in the number of machine cycles required to search for the necessary elements in the dynamic array was practically confirmed. This leads to an increase in the performance of the presented algorithm of binomial arithmetic addition based on dynamic arrays. In turn, this leads to the acceleration of solving information tasks of combinatorial optimization, generation of combinatorial objects, data compression and encryption, for the solution of which the operation of adding binary binomial numbers is used. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid development of intelligent technology, information security and privacy issues have become increasingly prominent. Epidemiological survey data (ESD) research plays a vital role in understanding the laws and trends of disease transmission. However, epidemiological investigations (EI) involve a large amount of privacy-sensitive data which, once leaked, will cause serious harm to individuals and society. Collecting EI data is also a huge task. To solve these problems and meet personalized privacy protection requirements in EIs, we improve the uOUE protocol based on utility-optimized local differential privacy to improve the efficiency and accuracy of data coding. At the same time, aiming at the collection and processing of ESD, a multidimensional epidemiological survey data aggregation scheme based on uOUE is designed. By using Paillier homomorphic encryption and an identity-based signature scheme to further prevent differential attacks and achieve multidimensional data aggregation, the safe, efficient, and accurate aggregation processing of ESD is executed. Through security proof and performance comparison, it is verified that our algorithm meets the requirements of local differential privacy and unbiased estimation. The experimental evaluation results on two data sets show that the algorithm has good practicability and accuracy in ESD collection and provides reliable and effective privacy protection. [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]

To adhere to and capitalize on the benefits of the FAIR (findable, accessible, interoperable, and reusable) principles in agricultural genome-to-phenome studies, it is crucial to address privacy and intellectual property issues that prevent sharing and reuse of data in research and industry. Direct sharing of genotype and phenotype data is often prohibited due to intellectual property and privacy concerns. Thus, there is a pressing need for encryption methods that obscure confidential aspects of the data, without affecting the outcomes of certain statistical analyses. A homomorphic encryption method for genotypes and phenotypes (HEGP) has been proposed for single-marker regression in genome-wide association studies (GWAS) using linear mixed models with Gaussian errors. This methodology permits frequentist likelihood-based parameter estimation and inference. In this paper, we extend HEGP to broader applications in genome-to-phenome analyses. We show that HEGP is suited to commonly used linear mixed models for genetic analyses of quantitative traits including genomic best linear unbiased prediction (GBLUP) and ridge-regression best linear unbiased prediction (RR-BLUP), as well as Bayesian variable selection methods (e.g. those in Bayesian Alphabet), for genetic parameter estimation, genomic prediction, and GWAS. By advancing the capabilities of HEGP, we offer researchers and industry professionals a secure and efficient approach for collaborative genomic analyses while preserving data confidentiality. [ABSTRACT FROM AUTHOR]

Microscale thermal signature control using incoherent heat sources remains challenging, despite recent advancements in plasmonic materials and phase-change materials. Inspired by leafhopper-generated brochosomes, we design binary metastructures functioning as pixel twins to achieve pixelated thermal signature control at the microscale. In the infrared range, the pixel twins exhibit distinct emissivities, creating thermal counterparts of "0-1" binary states for storing and displaying information. In the visible range, the engineered surface morphology of the pixel twins ensures similar scattering behaviors. This renders them visually indistinguishable, thereby concealing the stored information. The brochosome-like pixel twins are self-emitting when thermally excited. Their structure-enabled functions do not rely on the permittivities of specific materials, which distinguishes them from the conventional laser-illuminated plasmonic holographic metasurfaces. The unique combination of visible camouflage and infrared display offers a systemic solution to microscale spatial control of thermal signatures and has substantial implications for optical security, anticounterfeiting, and data encryption. [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]

Opioid use disorder is a growing public health concern in the United States, causing economic burden and hindered by stigma. New forms of data, including location data, may improve the effectiveness of interventions for preventing and treating opioid use disorder and/or misuse, increase access to treatment and address racial and ethnic disparities. This qualitative study aimed to identify factors that contribute to users' experience with a publicly available location-tracking mobile app - and investigate their privacy and ethical concerns. The study was conducted through two 15-minute interviews within a 48-h time frame. Participants were recruited from a pool of past research participants, Facebook ads, and referrals, and had to meet certain inclusion criteria related to opioid use disorder and/or misuse. The study had a final sample of 30 participants, 15 male and 15 female. The study suggests that a simple onboarding process and convenient experience can enhance participant adherence to the study app and other similar location-based research apps. However, the study also found that participants had concerns about privacy and transparency about locational privacy when sharing their location data. To improve the app, researchers suggest incorporating user behavior earlier in the app development stage. The study also highlights the importance of addressing ethical and privacy concerns such as limiting the types of collected data, incorporating data encryption and retention strategies, giving access to research staff only, and not sharing the data with third-party companies or law enforcement agencies to increase user satisfaction. [ABSTRACT FROM AUTHOR]

Home area network (HAN) devices send the electricity consumption and other important data to the smart meter that must remain confidential from other devices. This paper proposes a novel one-dimensional hybrid chaotic map. The proposed map shows excellent chaotic properties when analyzed by bifurcation diagram, Lyapunov exponent & Shannon entropy. We further design an encryption strategy for data transfers between the smart meter and HAN devices. The proposed encryption scheme uses the existing lightweight key management in advanced metering infrastructure (LKM-AMI) architecture for data transfers, in which the encrypted data is transferred through an insecure channel and private keys are provided by trusted third party (TTP) through secure channels. The 2-way communication between HAN devices and the smart meter sends messages that are encrypted by using the proposed novel hybrid one-dimensional chaotic map. The encryption strategy mainly consists of three steps. In the first step, the seed and the control parameters are initialized. The second phase generates two intermediate keys using the proposed hybrid chaotic map. In the last phase, we encrypt the message by applying permutation followed by diffusion using intermediate keys. The proposed encryption strategy is resistant to various attacks. [ABSTRACT FROM AUTHOR]

In order to address the problems of the single encryption algorithm, such as low encryption efficiency and unreliable metadata for static data storage of big data platforms in the cloud computing environment, we propose a Hadoop based big data secure storage scheme. Firstly, in order to disperse the NameNode service from a single server to multiple servers, we combine HDFS federation and HDFS high-availability mechanisms, and use the Zookeeper distributed coordination mechanism to coordinate each node to achieve dual-channel storage. Then, we improve the ECC encryption algorithm for the encryption of ordinary data, and adopt a homomorphic encryption algorithm to encrypt data that needs to be calculated. To accelerate the encryption, we adopt the dual-thread encryption mode. Finally, the HDFS control module is designed to combine the encryption algorithm with the storage model. Experimental results show that the proposed solution solves the problem of a single point of failure of metadata, performs well in terms of metadata reliability, and can realize the fault tolerance of the server. The improved encryption algorithm integrates the dual-channel storage mode, and the encryption storage efficiency improves by 27.6% on average.

The swift development of the Internet of Things (IoT) has accelerated digitalization across several industries, offering networked applications in fields such as security, home automation, logistics, and quality control. The growth of connected devices, on the other hand, raises worries about data breaches and security hazards. Because of IoT devices’ computational and energy limits, traditional cryptographic methods face issues. In this context, we emphasize the importance of our contribution to image encryption in IoT environments through the proposal of Multiple Map Chaos Based Image Encryption (MMCBIE), a novel method that leverages the power of multiple chaotic maps. MMCBIE uses multiple chaotic maps to construct a strong encryption framework that considers the inherent features of digital images. Our proposed method, MMCBIE, distinguishes itself by integrating multiple chaotic maps like Henon Chaotic Transform and 2D-Logistic Chaotic Transform in a novel combination, a unique approach that sets it apart from existing schemes. Compared to other chaotic-based encryption systems, this feature renders them practically indistinguishable from pure visual noise. Security evaluations and cryptanalysis confirm MMCBIE’s high-level security properties, indicating its superiority over existing image encryption techniques. MMCBIE demonstrated superior performance with NPCR (Number of Pixel Changing Rate) score of 99.603, UACI (Unified Average Changing Intensity) score of 32.8828, MSE (Mean Square Error) score of 6625.4198, RMSE (Root Mean Square Error) score of 80.0063, PSNR (Peak Signal to Noise Ratio) score of 10.2114, and other security analyses.

The edge devices will produce enormous quantities of data daily as the Industrial Internet of Things (IIoT) expands in scope. Still, most IIoT data is stored in data centers, making it challenging to transfer data between domains safely. Smart logistic products have dramatically changed due to the prevalence of decentralized edge computing and blockchain in the industry sector. To address the need to exchange data between logistics networks, we proposed a novel decentralized hierarchical attribute-based encryption (HABE) scheme combining edge computing and blockchain. To begin, we offer an IoT data encryption strategy in which edge devices can send data to a nearby cloud network for data processing while maintaining privacy. In addition, we developed a blockchain-integrated data-sharing scheme that makes it possible for users to share data via the use of edge and cloud storage. In particular, an IoT device incorporates an encryption-based authentication system to verify users’ access rights at the network’s periphery in a decentralized manner. Using HABE, we provide a blockchain-integrated architecture for the IoT that protects user privacy. The suggested design utilizes the edge and cloud network paradigms and HABE to maintain privacy and works well with smart logistics applications. The authentication time of the proposed model is reduced by 1.5 times compared with the centralized model. The analyses and experimental findings show that the proposed blockchain-integrated edge computing architecture is better than the existing schemes in terms of data sharing, data privacy, and security.

With the increasing use of optical fiber communication technology in the Industrial Internet of Things, cryptographic algorithms play a crucial role in ensuring the security of data transmission in embedded device environments.The SM4 packet cipher algorithm, developed independently in our country, is widely applied to wireless LAN and Internet of Things data encryption.However, the software-based encryption and decryption processes are relatively slow, which hampers their application in scenarios requiring high real-time performance, especially for embedded devices.To address this issue, a high-performance and secure optical fiber communication system was designed based on the FPGA platform and the SM4 algorithm.The FPGA was used to implement the MAC layer interface for SM4 algorithm encryption and decryption, as well as data transmission.Besides, an optimization scheme for the hardware implementation architecture of the SM4 algorithm was proposed.The critical path was shortened by employing a pipeline method, thereby improving the system clock frequency.Additionally, parallel processing of S-box transformation was accelerated to enable efficient data replacement.To reduce data reading delays, a dual-cache processing method was combined to facilitate easier processing of cache data and significantly reduce packet loss rates.This scheme greatly enhanced system data throughput.Experimental results demonstrate that compared to similar designs, the throughput of the SM4 algorithm encryption and decryption module in this scheme reaches up to 25.6 Gbit/s, with minimal differences in resource consumption.Due to limitations imposed by the 10-gigabit SFP+ optical module, the throughput of the entire optical fiber communication system reaches 9.4 Gbit/s.For 128-bit data, the average encryption speed is 0.47 μs/bit and the average decryption speed is 0.28 μs/bit, which can be applied to a variety of secure communication scenarios in the internet of things.

In this study, we present a new cryptosystem named Deoxyribose Nucleic Acid (DNA) secret writing with the Laplace transform of the Mittag-Leffler function. The method is proper for encrypting large files. In this technique, we consider the original message as binary sequence. These binary streams corresponding to the plain text is transformed to DNA bases by utilizing DNA encoding, then the DNA codes are transformed to positive integers. We apply the Laplace transform to these numbers which are coefficients of the expansion of the Mittag-Leffler function. To provide multi-stage protection, the outcome coefficients are transformed to binary sequences and other level of encryption with cumulative XOR is applied and equivalent MSBs obtained at every iteration are utilized for building cipher text. Decryption is implemented in the opposite way. We employ monobit test, correlation analysis for measuring the reliability of encryption, and Python programming language to obtain secret message, the plain text, and computations of statistical tests.

• A new optical image encryption and authentication scheme is proposed with the computational ghost imaging. • The problem of inherent linear defect and key management in computational ghost imaging encryption system is solved. • The dual-channel encryption method provides multi-layer protection for the plaintext images. Considering the necessity of identity authentication in most scenarios, a dual-channel (digital channel and optical channel) image encryption and authentication algorithm with computational ghost imaging (CGI) is proposed. The entire encryption process is governed by the pseudo-random sequences obtained by the 4D chaotic system and the Logistic map. During the digital channel encryption, the confusion and diffusion of the plaintext image are achieved by random scrambling and DNA computing, respectively. To alleviate the burden of key transmission and storage in the CGI encryption system, the speckle measurement matrices are constructed with the pseudo-random numbers obtained by the Logistic map. Additionally, a nonlinear encryption operation is carried out to compensate the linear vulnerability of CGI encryption. In the optical encryption channel, the authentication image is first encrypted with the CGI method, followed by the secondary encryption of the intensity values recorded by a bucket detector to produce an intermediate ciphertext. The final encryption image is generated by merging the intermediate ciphertexts from both encryption channels. It is demonstrated that the proposed optical image encryption and authentication scheme with CGI provides satisfactory encryption and decryption effects and can effectively counteract the common attacks. Moreover, the scheme holds promising application prospects due to its authentication capability. [ABSTRACT FROM AUTHOR]

With the continuous advancement of System-on-Chip (SoC) technologies, the burgeoning data volumes emphasize the paramount importance of safeguarding data security and integrity. In this study, by leveraging Ascon in conjunction with enhancements to the SHA-1 algorithm, two secure Direct Memory Access (DMA) controllers are designed to facilitate data encryption and comparison, respectively, culminating in the proposal of an SoC architecture featuring dual DMA controllers. Simulation outcomes demonstrate the system's ability to achieve a maximum clock frequency of 120 MHz, offering a throughput rate of up to 3.2 GB/s. The multi-master multi-slave AHB bus matrix within the system operates impeccably, ensuring smooth functionality. Furthermore, the two DMA controllers exhibit independent operation, featuring flexible start-stop capabilities. Notably, they operate harmoniously without conflicts, optimizing the area utilization while adhering to a low power consumption design methodology. The results unequivocally affirm the feasibility of designing a secure SoC integrated with two DMA controllers. This hardware-based approach effectively ensures data security, showcasing promising prospects for real-world applications. [ABSTRACT FROM AUTHOR]

The rapid development of new technologies such as artificial intelligence and big data analysis requires the simultaneous development of cloud computing technology. The application of IoT‐to‐cloud setting has been fully applied in various industry sectors, such as sensor‐cloud system which is composed of wireless sensor network and cloud computing technology. With the increasing amount and types of collected data, companies need to reduce the dimension of massive data in cloud servers for obtaining data analysis reports rapidly. Due to frequent cloud server data leaks, companies must adequately protect the privacy of some confidential data. To this end, we designed a dimension reduction method for ciphertext data in the sensor‐cloud system based on the CKKS encryption scheme, principal component analysis (PCA) and linear discriminant analysis (LDA) dimension reduction algorithm. As data cannot be directly calculated using traditional PCA and LDA algorithm after encryption, we add some interactive operations and iterative calculations to replace some steps in traditional algorithms. Finally, we select the classification dataset IRIS which is commonly used in machine learning, and screen out the best encryption and calculation parameters, and efficiently realize the dimension reduction method of ciphertext data through a large number of experiments. [ABSTRACT FROM AUTHOR]

Polymer‐based room‐temperature phosphorescence (RTP) materials, especially polysaccharide‐based RTP materials, earn sustained attention in the fields of anti‐counterfeiting, data encryption, and optoelectronics owing to their green regeneration, flexibility, and transparency. However, those with both ultralong phosphorescence lifetime and excitation wavelength‐dependent afterglow are rarely reported. Herein, a kind of amorphous RTP material with ultralong lifetime of up to 2.52 s is fabricated by covalently bonding sodium alginate (SA) with arylboronic acid in the aqueous phase. The resulting polymer film exhibits distinguished RTP performance with excitation‐dependent emissions from cyan to green. Specifically, by co‐doping with other fluorescent dyes, further regulation of the afterglow color from cyan to yellowish‐green and near‐white can be achieved through triplet‐to‐singlet Förster resonance energy transfer. In addition, the water‐sensitive properties of hydrogen bonds endow the RTP property of SA‐based materials with water/heat‐responsive characteristics. On account of the color‐tunable and stimuli‐responsive afterglows, these smart materials are successfully applied in data encryption and anti‐counterfeiting. [ABSTRACT FROM AUTHOR]