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Enhanced computations resulted in the evolution of cyber-physical systems (CPS). These systems are highly vulnerable to security threats. This work addresses the security concerns for a reliable CPS in the Internet of Things (IoT) through an improvised RSA with enhanced security features. The proposed method renders data throughput encryption at 11.67Kbps with an overall average execution time of 0.02s. The proposed algorithm exhibits the unique feature of being asymmetric, lightweight & enhanced security owing to randomization (average entropy of 0.98). The performance metrics of the proposed method are compared with other state-of-art techniques. This algorithm is implemented on commercially competent architecture STM32F401RET6 with cortex M4 processor running @ 84MHz. The proposed encryption method exhibits great features thus making it a potential real-world solution. [ABSTRACT FROM AUTHOR]

The study of small organic molecules that have different molecular structures with the same luminescent core, which produces fluorescence, phosphorescence or delayed fluorescence, is fascinating. Of course, the regulation of elaborate chemical structures is a reliable way to achieve these emission properties. In this study, five carbazole derivatives with different functional groups were obtained via C–N coupling reactions: Cz–C8, Cz–C8–Br, Cz–C8–OH, Cz–C8–Tu and Cz–C7–COOH. Our results reveal that small differences in functionalized tail groups can produce a huge contrast in photoluminescence behavior. Obviously, more polar tails, such as −Tu and −COOH, contribute more to high-performance organic room temperature phosphorescent materials. The non-polar tail of –H favors delayed fluorescence, while the mid-polar group of –OH enables phosphorescence and delayed fluorescence in Cz–C8–OH. These two different behaviors can be artificially modulated by external stimuli, such as photoactivation and thermal annealing. A study of the internal mechanism shows that intermolecular interactions and the molecular aggregation state are the main factors affecting the photoluminescence performance. Finally, advanced applications in the fields of data encryption, data storage, and anti-counterfeiting are illustrated using time-resolved techniques. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Duration‐tunable afterglow materials have garnered considerable attention in various applications. Herein, carbon dots (CDs)‐based long persistent luminescence (LPL) composites with a tunable duration in an ultrawide range of seconds‐to‐hours levels were designed and prepared for the first time. In contrast to the established CD‐based afterglow materials, we reported that CD‐based composites exhibit LPL in the form of exciplexes and long‐lived charge‐separated states, enabling the LPL to be prolonged from several seconds to over one hour, exceeding the typical regulation range (limited to 1 min). Further studies revealed that the relationship between the excited and charge‐transfer states of CDs plays a pivotal role in activating the LPL and regulating its duration. Furthermore, these composites exhibited high photoluminescence (PL) quantum yields of up to 60.63%, and their LPL was robust under ambient conditions, even in aqueous media. Their robust and superior LPL performance endows these composites with a strong competitive advantage in dynamic display systems, such as tags for time‐resolved data encryption and displays of the remaining time of takeaways. This study offers an approach to preparing CDs‐based LPL composites with tunable durations and may provide new insights for the development of rare‐earth‐free LPL materials. [ABSTRACT FROM AUTHOR]

Medical data sharing is pivotal in enhancing accessibility and collaboration among healthcare providers, researchers, and institutions, ultimately leading to enhanced patient outcomes and more efficient healthcare delivery. However, due to the sensitive nature of medical information, ensuring both privacy and confidentiality is paramount. Access control-based data sharing methods have been explored to address these issues, but data privacy concerns still remain. Therefore, this paper proposes a secure and privacy-preserving data sharing scheme that achieves an equilibrium between data confidentiality and privacy. By leveraging key aggregate encryption and private set intersection techniques, our scheme ensures secure data sharing while protecting against the exposure of sensitive information related to data. We conduct informal and formal security analyses, including Burrow–Abadi–Needham logic and Scyther, to demonstrate its resilience against potential adversarial attacks. We also implement the execution time for cryptographic operations using multiprecision integer and a rational arithmetic cryptographic library and perform comparative analysis with existing related schemes in terms of security, computational cost, and time complexity. Our findings demonstrate a high level of security and efficiency, demonstrating that the proposed scheme contributes to the field by providing a solution that protects data privacy while enabling secure and flexible sharing of medical data. [ABSTRACT FROM AUTHOR]

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

Nowadays, the omnipresence of the Internet has fostered a subculture that congregates around the contemporary milieu. The subculture artfully articulates the intricacies of human feelings by ardently pursuing the allure of novelty, a fact that cannot be disregarded in the sentiment analysis. This paper aims to enrich data through the lens of subculture, to address the insufficient training data faced by sentiment analysis. To this end, a new approach of subculture‐based data augmentation (SCDA) is proposed, which engenders enhanced texts for each training text by leveraging the creation of specific subcultural expression generators. The extensive experiments attest to the effectiveness and potential of SCDA. The results also shed light on the phenomenon that disparate subcultural expressions elicit varying degrees of sentiment stimulation. Moreover, an intriguing conjecture arises, suggesting the linear reversibility of certain subcultural expressions. [ABSTRACT FROM AUTHOR]

In recent years, Censorship and anti-censorship technology is developing rapidly. The censorship and surveillance systems track traffic on the network; they identify protocols and traffic, block malicious and illegal transportation, and keep the network under control. It can protect the security of network users but also bring risks to their private security, especially that of users chat. In this paper, we introduce MuChat, a free convert chat application for instant communication on mobile, which is designed as censorship as well as surveillance-resistant platform for coverting communication in the censorship region. To evade detection by Internet censors, MuChat uses multi-instant messaging channels provided by public companies to transform messages. It applies end-to-end encryption for information security and transmits data covertly by steganography technology for individual privacy. It also provides perfect forward security protection of users' historical messages. We design and implement MuChat, with this report on the security and performance of MuChat. The evaluation shows that MuChat has proved its high security in terms of running against active attacks, passive attacks, and traffic analysis methods in recent years. It supports all the functions of instant messages with low latency. For short words, it takes only 1–2 s while the base channels take about 0.5 s, and for 20-megabyte files messages with 35–45 s while about 30–40 s for base channels. In our view, this meets the instant communication needs of users. Besides, its architecture can fully support any other public communication channels which can be added by the user. [ABSTRACT FROM AUTHOR]

The smart grid, as a crucial part of modern energy systems, handles extensive and diverse data, including inputs from various sensors, metering devices, and user interactions. Outsourcing data storage to remote cloud servers presents an economical solution for enhancing data management within the smart grid ecosystem. However, ensuring data privacy before transmitting it to the cloud is a critical consideration. Therefore, it is common practice to encrypt the data before uploading them to the cloud. While encryption provides data confidentiality, it may also introduce potential issues such as limiting data owners' ability to query their data. The searchable attribute-based encryption (SABE) not only enables fine-grained access control in a dynamic large-scale environment but also allows for data searches on the ciphertext domain, making it an effective tool for cloud data sharing. Although SABE has become a research hotspot, existing schemes often have limitations in terms of computing efficiency on the client side, weak security of the ciphertext and the trapdoor. To address these issues, we propose an efficient server-aided ciphertext-policy searchable attribute-based encryption scheme (SA-CP-SABE). In SA-CP-SABE, the user's data access authority is consistent with the search authority. During the search process, calculations are performed not only to determine whether the ciphertext matches the keyword in the trapdoor, but also to assist subsequent user ciphertext decryption by reducing computational complexity. Our scheme has been proven under the random oracle model to achieve the indistinguishability of the ciphertext and the trapdoor and to resist keyword-guessing attacks. Finally, the performance analysis and simulation of the proposed scheme are provided, and the results show that it performs with high efficiency. [ABSTRACT FROM AUTHOR]

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

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]

A confidential reporting system (CRS) allows reporters to report concerns or problems in confidence without the fear of blame or reprisals. Nevertheless, privacy has been the primary concern of reporters. In this paper, we propose a privacy-preserving confidential reporting system with designated reporters (PPCRS-DR) to protect the privacy of reporters and the confidentiality of reports. Our PPCRS-DR provides the following interesting features: (1) for an event, an auditor can designate a reporter to report; (2) an auditor can neither see the report nor know the reporter's identity from an encrypted report if the reporter is not the designated one; (3) when an auditor is unavailable, he/she can temporarily designate a delegatee to collect and review reports on behalf of him/her. We formalize both the definition and security model of our PPCRS-DR, and propose a concrete construction. Furthermore, the security of the proposed PPCRS-DR is formally proven. The implementation shows that it is efficient. The novelty is to implement flexible decryption delegation of CRSs and protect reporters' privacy. [ABSTRACT FROM AUTHOR]

The |$k$| th min threshold is to judge whether the |$k$| th smallest element of an attribute set along with a confidential file is greater than a predefined threshold, which is a fundamental, primitive operation in data evaluation, such as risk evaluation in business investment. However, it will compromise the privacy of the confidential files when proceeding with such a data evaluation because there is often a large amount of sensitive information involved in them, which the organizations/individuals are reluctant to expose due to the risk of losing a competitive advantage. Motivated by the issue how to preserve the privacy of the confidential files during data evaluation, in this research, we first present a new encryption notion called |$k$| th min threshold encryption (KTE) for serving privacy-preserving data evaluation. In this notion, the confidential file will be encrypted under an attribute set for its privacy protection prior to being sent to a receiver, and a decryption key is generated from a threshold |$d$| and a rank |$k$| of element, both selected by the receiver. The decryption will be successful if and only if the |$k$| th smallest element of the attribute set is greater than |$d$|⁠. We then describe a concrete construction of KTE in the public-key setting. In particular, our construction features optimally short private keys, which only consists of one group element. By virtue of this advantage, it is quite practical because of only two pairing operations for decryption computation. [ABSTRACT FROM AUTHOR]

Privacy-preserving smart meter data collection and analysis are critical for optimizing smart grid environments without compromising privacy. Using homomorphic encryption techniques, smart meters can encrypt collected data to ensure confidentiality, and other untrusted nodes can further compute over the encrypted data without having to recover the underlying plaintext. As an illustrative example, this approach can be useful to compute the monthly electricity consumption without violating consumer privacy by collecting fine-granular data through small increments of time. Toward that end, we propose an architecture for privacy-preserving smart meter data collection, aggregation and analysis based on lattice-based homomorphic encryption. Furthermore, we compare the proposed method with the Paillier and Boneh–Goh–Nissim (BGN) cryptosystems, which are popular alternatives for homomorphic encryption in smart grids. We consider different services with different requirements in terms of multiplicative depth, e.g. billing, variance and nonlinear support vector machine classification. Accordingly, we measure and show the practical overhead of using the proposed homomorphic encryption method in terms of communication traffic (ciphertext size) and latency. Our results show that lattice-based homomorphic encryption is more efficient than Paillier and BGN for both multiplication and addition operations while offering more flexibility in terms of the computation that can be evaluated homomorphically. [ABSTRACT FROM AUTHOR]

The healthcare systems follow the path of client-server architecture in a centralized manner for managing the patient's health information with the secure storage process. Medical data can be preserved in every medical institution that remains safely in silos. It could be able to access without proper authorization and cannot be transferred. At the same time, while handling massive data, the clinics or hospitals are fragile enough to govern the patient's health information as the system is confined with such security constraints. Rather than other methodologies, blockchain plays a pivotal part in the medical industry for storing medical data in a secure manner. Since the blockchain represents a reliable and scalable decentralized network, it can conquer certain challenges of classical methods. Furthermore, the Internet of Things (IoT) is an emerging process of fetching data by wearing some sensors and devices. Through these intelligent elements, the healthcare data can be shared and enriched with the data quality for effective healthcare services. Nevertheless, this connection becomes vulnerable to data privacy and security because the data management relies on open service networks. In order to overcome these effects, a novel IoT-derived blockchain model is proposed for storing and authenticating purposes. Initially, medical data are collected from different benchmark sources and subjected to the data encryption phase. Then, encryption is performed with the help of Adaptive Elliptical Curve Cryptography and Rivest-Shamir-Adleman (A-ECC-RSA), where the key optimization is done by utilizing Enhanced Sand Cat Swarm Optimization (ESCSO). Further, encrypted data are stored in the blockchain and finally authentication access is performed with the help of Adaptive Bidirectional Long Short-Term Memory (ABiLSTM) using biometric information, where the BiLSTM parameters are optimally selected by developed ESCSO. Thus, the developed model will attain an effective security rate than conventional models that can be established through several experiments on the proposed model. [ABSTRACT FROM AUTHOR]

Quantum computing advancements pose security challenges for cryptography. Specifically, Grover's search algorithm affects the reduction in the search complexity of symmetric-key encryption and hash functions. Recent efforts have been made to estimate the complexity of Grover's search and evaluate post-quantum security. In this paper, we propose a depth-optimized quantum circuit implementation for ASCON, including both symmetric-key encryption and hashing algorithms, as a part of the lightweight cryptography standardization by NIST (National Institute of Standards and Technology). As far as we know, this is the first implementation of a quantum circuit for the ASCON AEAD (Authenticated Encryption with Associated Data) scheme, which is a symmetric-key algorithm. Also, our quantum circuit implementation of the ASCON-HASH achieves a reduction of more than 88.9% in the Toffoli depth and more than 80.5% in the full depth compared to the previous work. As per our understanding, the most effective strategy against Grover's search involves minimizing the depth of the quantum circuit for the target cipher. We showcase the optimal Grover's search cost for ASCON and introduce a proposed quantum circuit optimized for depth. Furthermore, we utilize the estimated cost to evaluate post-quantum security strength of ASCON, employing the relevant evaluation criteria and the latest advancements in research. [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]

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]

DNA‐based hybrid materials have attracted much attention recently for their biocompatibility, tunable optical, and semiconducting properties. In this study, thin films fabricated using native DNA are modified to accommodate the assembled fluorescent dyes (perylene and 3‐bromoperylene), alongside the systematical evaluation of their photophysical properties and performance. Spectroscopy results reveal successful modulation of the molecular excitonic behaviour, achieve switchable single‐chromophore multi‐color emission in DNA‐surfactant‐dye thin films, with high optical transparency and thermal robustness. The nucleotide base pairs effectively suppress unfavorable intermolecular π–π stacking and aggregation (self‐association) of the chromophores, which prevents intersystem crossing and relaxation associated Rydberg type molecular clusters to form intermolecular excimers in E‐state (532, 513 nm) and Y‐state (489, 483 nm), blocking nonradiative decay. The preeminent emission observed (457, 445 nm) is attributed to the 0–1 band monomer emission. Compared to PMMA‐dye assembly, the thin film derived from DNA‐surfactant‐dye hybrid narrows the FWHM values up to 72%, displayed molarity ratio‐dependent emission color tunability from yellow‐orange (CIE 0.47, 0.34) to green (CIE 0.31, 0.21) and blue (CIE 0.17, 0.23). These findings provide a simple, all‐solution processed strategy for creating thin films using DNA‐surfactant‐dye hybrid materials with tunable optical properties suitable for biocompatible displays and data encryption. [ABSTRACT FROM AUTHOR]

With the continuous advancement of information technology, a growing number of works, including articles, paintings, and music, are being digitized. Digital content can be swiftly shared and disseminated via the Internet. However, it is also vulnerable to malicious plagiarism, which can seriously infringe upon the rights of creators and dampen their enthusiasm. To protect creators' rights and interests, a sophisticated method is necessary to authenticate digital intellectual property rights. Traditional authentication methods rely on centralized, trustworthy organizations that are susceptible to single points of failure. Additionally, these methods are prone to network attacks that can lead to data loss, tampering, or leakage. Moreover, the circulation of copyright information often lacks transparency and traceability in traditional systems, which leads to information asymmetry and prevents creators from controlling the use and protection of their personal information during the authentication process. Blockchain technology, with its decentralized, tamper-proof, and traceable attributes, addresses these issues perfectly. In blockchain technology, each node is a peer, ensuring the symmetry of information. However, the transparent feature of blockchains can lead to the leakage of user privacy data. Therefore, this study designs and implements an Ethereum blockchain-based intellectual property authentication scheme with privacy protection. Firstly, we propose a method that combines elliptic curve cryptography (ECC) encryption with digital signatures to achieve selective encryption of user personal information. Subsequently, an authentication algorithm based on Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARK) is adopted to complete the authentication of intellectual property ownership while encrypting personal privacy data. Finally, we adopt the InterPlanetary File System (IPFS) to store large files, solving the problem of blockchain storage space limitations. [ABSTRACT FROM AUTHOR]

Researchers have created cryptography algorithms that encrypt data using a public or private key to secure it from intruders. It is insufficient to protect the data by using such a key. No research article has identified an algorithm capable of protecting both the data and the associated key, nor has any mechanism been developed to determine whether access to the data is permissible or impermissible based on the authentication of the key. This paper presents a WEDEx-Kerberotic Framework for data protection, in which a user-defined key is firstly converted to a cipher key using the "Secure Words on Joining Key (SWJK)" algorithm. Subsequently, a WEDEx-Kerberotic encryption mechanism is created to protect the data by encrypting it with the cipher key. The first reason for making the WEDEx-Kerberotic Framework is to convert the user-defined key into a key that has nothing to do with the original key, and the length of the cipher key is much shorter than the original key. The second reason is that each ciphertext and key value are interlinked. When an intruder utilizes the snatching mechanism to obtain data, the attacker obtains data or a key unrelated to the original data. No matter how efficient the algorithm is, an attacker cannot access the data when these methods and algorithms are used to protect it. Finally, the proposed algorithm is compared to the previous approaches to determine the uniqueness of the algorithm and assess its superiority to the previous algorithms. [ABSTRACT FROM AUTHOR]

Smart thermal emission, which is response to external stimuli, has provided an unparalleled approach to exploiting optical devices that allows for tunable photon radiance. Here, an approach of implementing information encryptions using a smart thermal emission material that exhibits non‐volatile, multifunctional, and on‐chip‐integrable properties is reported. The smart material is a bilayer structure, consisting of a tungsten (W)‐doped vanadium dioxide (VO2) thin film layer and a self‐assembled polystyrene (PS) microsphere layer. Significant differences between the phase transition temperatures of differently doped VO2 films enable reconfigurable thermal emission in response to heat. Levels of information recorded by the patterning of these VO2 films are thus encrypted thermo‐radiatively. Additionally, the structural color of PS layer, as a result of photonic crystal bandgap effect, shades the encoded patterns from visible observation, and provides an anti‐counterfeiting function. Notable observation angle independence and device‐friendly encoding processes are also demonstrated. Based on these thermo‐tunable emission characteristics, the concept of multilevel data encryption via infrared radiation detection, temperature dependence, and visible anti‐counterfeiting, is realized by the smart bilayer material. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) and blockchain technology have emerged as increasingly prevalent and influential elements shaping global trends in Information and Communications Technology (ICT). Namely, the synergistic combination of blockchain and AI introduces beneficial, unique features with the potential to enhance the performance and efficiency of existing ICT systems. However, presently, the confluence of these two disruptive technologies remains in a rather nascent stage, undergoing continuous exploration and study. In this context, the work at hand offers insight regarding the most significant features of the AI and blockchain intersection. Sixteen outstanding, recent articles exploring the combination of AI and blockchain technology have been systematically selected and thoroughly investigated. From them, fourteen key features have been extracted, including data security and privacy, data encryption, data sharing, decentralized intelligent systems, efficiency, automated decision systems, collective decision making, scalability, system security, transparency, sustainability, device cooperation, and mining hardware design. Moreover, drawing upon the related literature stemming from major digital databases, we constructed a timeline of this technological convergence comprising three eras: emerging, convergence, and application. For the convergence era, we categorized the pertinent features into three primary groups: data manipulation, potential applicability to legacy systems, and hardware issues. For the application era, we elaborate on the impact of this technology fusion from the perspective of five distinct focus areas, from Internet of Things applications and cybersecurity, to finance, energy, and smart cities. This multifaceted, but succinct analysis is instrumental in delineating the timeline of AI and blockchain convergence and pinpointing the unique characteristics inherent in their integration. The paper culminates by highlighting the prevailing challenges and unresolved questions in blockchain and AI-based systems, thereby charting potential avenues for future scholarly inquiry. [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]

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]

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]

Privacy is given top priority as far as communication involving transfer of confidential document or data is concerned. There is therefore a need to keep confidential data secretive from being invaded by unauthorised access, and this is done through cryptography algorithms, where the Advanced Encryption Standard algorithm has been the widely accepted symmetric block encryption algorithm for such purposes. This paper therefore focuses on developing a new AES-512 bits symmetric encryption algorithm through modification of the conventional AES-128 algorithm to be used purposefully in the classroom for document transfer. The development comes with increasing the plaintext bits of the conventional AES-128 algorithm to 512 bits plaintext which undergoes five operational transformations: STATE, SKGF, SRL, SCL and AARC through key size in the Galois field, GF(29 ). A numerical example is then given to explain the use of the algorithm, and finally, we provide a comparative study of this algorithm and other existing symmetric encryption models, such as the AES-128 and DES algorithms. [ABSTRACT FROM AUTHOR]

The sensing-as-a-service concept has been developed to address the challenges that future smart cities would have in managing an enormous number of sensors. Smart cities must find a solution to the enormous difficulty of effectively sharing user-confidential information without sacrificing quality, privacy, or interruption. The development of blockchain technology has the potential to overcome these problems, but the limitations of the current models include large storage, customizable blockchain, high communication overhead, and high processing costs. The proposed average hybrid leader optimization (AHLO)-PrivPresKey Gen model determined a blockchain-based secure information sharing scheme using a smart contract in a smart city. Blockchain-based smart contracts implement a highly complex midway illustration method to reduce the user's clarification burden. The proposed scheme makes utilize of different safety operators, like 3 Data Encryption Standard, segmenting interpolation, passwords, one time password token and etc. Furthermore, the data privacy phase is improved by utilizing various functionalities, such as dyadic product, Chebyshev polynomial, and keys, where the keys are optimally generated using AHLO. The designed AHLO is obtained by the consolidation of average and subtraction based optimizer and hybrid leader-based optimization. The designed model has delivered minimum memory of 30.5 MB, minimum computational time of 28.467 MB, maximum encryption quality of 0.808, maximum detection rate of 0.898, minimum responsiveness of 41.679 and minimum bandwidth of 95 that surpasses the conventional schemes. [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]

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]

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]

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]

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 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]

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]

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]

Cloud Service Providers, exemplified by industry leaders like Google Cloud Platform, Microsoft Azure, and Amazon Web Services, deliver a dynamic array of cloud services in an ever-evolving landscape. This sector is witnessing substantial growth, with enterprises such as Netflix and PayPal heavily relying on cloud infrastructure for various needs such as data storage, computational resources, and various other services. The adoption of cloud solutions by businesses not only facilitates cost reduction but also fosters flexibility and supports scalability. Despite the undeniable advantages, concerns surrounding security and privacy persist in the realm of Cloud Computing. Given that Cloud services are accessible via the internet, there is a potential vulnerability to unauthorized access by hackers or malicious entities from anywhere in the world. A crucial aspect of addressing this challenge is the implementation of robust security measures, particularly focusing on data protection. To safeguard data in the Cloud, a fundamental recommendation is the encryption of data prior to uploading. Encryption should be maintained consistently, both during storage and in transit. While encryption enhances security, it introduces a potential challenge for data owners who may need to perform various operations on their encrypted data, such as accessing, modifying, updating, deleting, reading, searching, or sharing them with others. One viable solution to balance the need for data security and operational functionality is the adoption of Searchable Encryption (SE). SE operates on encrypted data, allowing authorized users to perform certain operations without compromising the security of sensitive information. The effectiveness of SE has notably advanced since its inception, and ongoing research endeavors aim to further enhance its capabilities. This paper provides a comprehensive review of the functionality of Searchable Encryption, with a primary focus on its applications in Cloud services during the period spanning 2019 to 2023. Additionally, the study evaluates one of its prominent schemes, namely Fully Homomorphic Encryption (FHE). The analysis indicates an overall positive trajectory in SE research, showcasing increased efficiency as multiple functionalities are aggregated and rigorously tested. [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]

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]

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]

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 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]

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]

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]

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 key distribution (QKD) is one quantum technology that can provide secure encryption keys for data transmission. The secret key rate (SKR) is a core performance indicator in QKD, which directly determines the transmission rate of enciphered data. Here, for the first time, we demonstrate a high-key-rate Gaussian-modulated continuous-variable QKD (CV-QKD) using telecom optical components. The framework of CV-QKD over these components is constructed. Specifically, the high-rate low-noise Gaussian modulation of coherent states is realized by a classical optical IQ modulator. High-baud low-intensity quantum signals are received by an integrated coherent receiver under the shot-noise limit. A series of digital signal processing algorithms are proposed to achieve accurate signal recovery and key distillation. The system can yield a high asymptotic SKR of 10.37 Mbps within 20 km standard telecom fiber, and the secure distance can exceed 100 km. This result confirms the feasibility of CV-QKD with state-of-the-art performance using telecom optical components. Besides, due to the ease of integrating these discrete components, it provides a high-performance and miniaturized QKD solution for the metropolitan quantum network. [ABSTRACT FROM AUTHOR]