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It remains challenging to elucidate the fundamental mechanisms behind the dynamic chirality inversion of supramolecular assemblies with pathway complexity. Herein, metal coordination driven assembly systems based on pyridyl-conjugated cholesterol (PVPCC) and metal ions (Ag+ or Al3+) are established to demonstrate pathway-directed, recyclable chirality inversion and assembly polymorphism. In the Ag(I)/PVPCC system, a competitive pathway leads Ag-Complex to form either kinetically controlled supramolecular polymer (Ag-SP I) or thermodynamically favored Ag-SP II, accompanied by reversible chiroptical inversion. Conversely, the Al(III)/PVPCC system displays a solvent-assisted consecutive pathway: the Al-Complex initially forms ethanol-containing Al-SP II, and subsequently converts into ethanol-free Al-SP I with opposite chiroptical performance upon thermal treatment. Moreover, stable chirality inversion in the solid state enables potential dynamic circularly polarized luminescence encryption when Ag(I)/PVPCC is co-assembled with thioflavin T. These findings provide the guidance for the dynamic modulation of chirality functionality in supramolecular materials for applications in information processing, data encryption, and chiral spintronics. Elucidation of the fundamental mechanisms behind the dynamic chirality inversion of supramolecular assemblies with pathway complexity is challenging. Here, the authors report metal coordination driven assembly systems based on pyridyl-conjugated cholesterol and show that metal ions facilitate pathway-directed, recyclable chirality inversion and assembly polymorphism. [ABSTRACT FROM AUTHOR]

Vehicular ad‐hoc networks (VANETs) support features like comfort, safety, and infotainment, enhancing traffic efficiency. However, traditional VANETs struggle with dynamic and large‐scale networks due to fixed policies and complex architectures, such as constantly changing vehicle positions. Software‐defined networks (SDN) can address these challenges by offering centralized, logical control, making VANETs more flexible and programmable. While SDNs improve VANET efficiency and add security benefits, they also introduce new security risks by incorporating novel technologies and architectural elements. Since VANET services rely heavily on data communication, compromised data (e.g., modified, falsified) could significantly impact driver and vehicle safety, making secure communication vital. Security threats specific to SDNs, like vulnerabilities in centralized control or flow‐based threats exploiting dynamic routing, necessitate robust cryptographic solutions to secure vehicle communications and data exchange. Various cryptographic algorithms, differing in performance, speed, memory requirements, and key sizes, pose challenges in selecting the optimal one for SDN‐based VANETs. This study evaluated seven cryptographic algorithms, including Blowfish, data encryption standard, triple data encryption standard, Rivest–Shamir–Adleman, advanced encryption standard (AES), advanced encryption standard with elliptic curve cryptography (AES‐ECC), and advanced encryption standard with elliptic curve Diffie‐Hellman (AES‐ECDH), in a simulated SDN‐based VANET. The findings show AES‐ECDH as the most effective overall, though the best choice depends on specific deployment scenarios and application needs. [ABSTRACT FROM AUTHOR]

In today's era, the pharmaceutical industry has integrated blockchain to secure the sensitive information of medicines, wherein public and private blockchains are used to preserve the security and privacy of the medicine supply chain data. However, conventional blockchains often limit scalability due to limited storage. Moreover, blockchain has loopholes; for example, it is not able to prove the validity of the data prior to being stored in the blockchain, which leads to fake data being added to the blockchain. As a result, it causes an issue of data provenance. Motivated by this, the proposed framework incorporated artificial intelligence (AI) algorithms to enhance the efficiency of the medicine supply chain data. The proposed framework integrated machine learning (ML) and blockchain, where ML classifies the valid and invalid data of the medicine supply chain, whereas blockchain stores only valid data and maintains its security and privacy. This identification helps the blockchain to verify medicine supply chain data before adding it to the blockchain. Additionally, we employed an InterPlanetary file system (IPFS) that saves medicine supply chain data and computes its hash to offer decentralized storage. Further, this hash data is stored on a private Hyperledger Fabric blockchain, which requires minimal storage instead of storing an entire large file. This minimal storage optimizes the process of data storage and retrieval in the Hyperledger Fabric blockchain, which enhances the scalability of the proposed framework. Finally, the result of the proposed framework is assessed in two phases: ML and blockchain, wherein the ML model's performance is measured by statistical measures and the blockchain‐based result is assessed using several performance parameters such as throughput is around (618 transactions per second), latency (0.12 s), response time (11 s) and data rate (282 Mbps). [ABSTRACT FROM AUTHOR]

The bidirectional asymmetric transmission (BAT) meta‐devices have attracted widespread attention as an emerging display, encryption, and information storage platform. Generally, the multiplexing capability of BAT meta‐devices determines the upper limit of the loading capacity of multi‐task integrated systems. However, existing BAT meta‐devices still depend on structural properties and the arrangement of meta‐atoms, limiting the number of manipulated channels, operating frequency, and polarization combinations. Herein, a universal BAT meta‐device, enabling bidirectional eight‐phase‐channel asymmetric transmission, composed of bilayer spatially cascaded birefringent metasurfaces (BMs) is proposed to allow for arbitrary polarization combination via the inverse design method and validated in the microwave region. In addition, the polarization multiplexing capabilities of BAT meta‐devices are further extended via a Lego‐like physical mechanism. The proposed design strategy may facilitate BAT meta‐devices functional innovation and advanced application deployment in holographic images, duplex communication, and secret‐key‐sharing data encryption. [ABSTRACT FROM AUTHOR]

Traditional anti‐counterfeiting luminescent phosphors are usually composed of single‐mode photoluminescence materials, which greatly limits the security of encryption by its static fluorescent pattern. Herein, multi‐mode luminescence properties are achieved including fluorescence and persistent luminescence (PersL) within single host by co‐doping Bi3+ and Eu3+ in CaNaSb2O6F (CNSOF). A tunable emission is observed from blue (Bi3+, 3P1→1S0) to white and then to orange‐yellow (Eu3+, 5D1→7F2 and 5D0→7F0, 1, 2, 3, 4) as the excitation schemes, environment temperatures and doping level are modulated. Impressively, the blue emission attributed to the Bi3+ rapidly disappears after stopping the excitation light irradiation, and only the intense orange‐yellow PersL produced by Eu3+ can be observed. And a possible model for the energy transfer and PersL mechanism is proposed by the investigation crystal structure and photoluminescence/PersL. A schematic of security logo and digital information encryption is demonstrated using the prepared samples, which shows the dynamic evolution of the emission color and PersL brightness. The excellent property of multiple color outputs, different decay processes, and external field stimulation modes (including low energy light, thermal, and mechanical stimuli) present in CNSOF:Bi3+, Eu3+ provides a fast, low‐cost, and effective method for advanced anti‐counterfeiting and information encryption applications. [ABSTRACT FROM AUTHOR]

Although different chemistries for the spatio‐temporal localization of molecules and gradients of chemical signals within soft materials are now available, the achievement of spatio‐temporal patterns of mechanical properties in such materials and their characterization remain considerable challenges. This study presents the syntheses of two novel photo‐sensitive and thermoresponsive hydrogel systems, a photo‐stiffening and a photo‐softening hydrogel. Their potential for fabricating soft materials with patterned mechanical properties is then demonstrated by fabricating an actuator whose higher‐order bending properties can be switched on with light, and by encoding mechanical properties for digital information encryption and storage. Microindentation and a custom‐made data analysis software are essential for the characterization of all the materials. From a general perspective, this work opens a route to the fabrication of soft materials with patterned mechanical properties, addressing an important emerging challenge in soft materials science with applications in soft robotics and information encryption and storage. [ABSTRACT FROM AUTHOR]

With the development of geographic information services, applications based on map data are increasing. Internet and mobile communication technologies have brought great convenience to the distribution, sharing, and acquisition of map data. Unfortunately, it also brings great challenges to protect the security and privacy of confidential map data. Although several encryption algorithms have been developed for map data, most of the existing methods are simple extensions of classical encryption algorithms for text data in cryptography, ignoring special structures and characteristics of geospatial data. Existing methods mainly take the entire map or layers as encryption units, which makes the encryption efficiency for large-scale map data low and limits the ability to perform local and incremental encryption for local areas, making it still challenging to meet the needs of map data in applications, such as autonomous driving. To solve the limitations, a local encryption approach for large-scale vector map data is proposed in this paper considering the structure characteristics of map data. Experiments on map data of different types (including points, lines, and polygons) demonstrate the effectiveness of the proposed method. With local and parallel encryption strategies, the proposed method has higher efficiency compared to available algorithms for large-scale map data. HIGHLIGHTS: A local encryption approach for vector map data is proposed, which can be applied to large-scale vector map data and support localized encryption/decryption for user-interested areas instead of the whole map data. The proposed method estimates different encryption parameters for different units which could significantly enhance the resistance to attacks and naturally supports parallel computing. With local and parallel encryption strategies, the proposed method has higher efficiency compared to available algorithms for large-scale map data. The method has great value and potential for ensuring map data security in ubiquitous GIS-based applications, such as map data sharing and dynamic updating in automatic driving and crowdsourced mapping. [ABSTRACT FROM AUTHOR]

Chatbot is an artificial intelligence application that can provide a conversational environment between humans and machines. Most organizations and industries are willing to lay out their services through chatbots because they can provide 24/7 customer support. Meanwhile, it raises security and privacy challenges like access control, data leakage during transmission, SQL injection attacks, and language model attacks, which make the users concerned about their data, performance, and accuracy. Therefore, this research paper proposes a comprehensive framework integrating blockchain, federated learning, and a fully homomorphic encryption algorithm with face recognition to solve the above-mentioned chatbot's challenges. The experimental result shows that a distributed system improves chatbot accuracy (90%) and that more transactions in less time with more clients do not affect the performance. In contrast, more iterations and clients will decrease the accuracy, performance, and transactions in a centralized system. In addition, fully homomorphic encryption improves and speeds up the data encryption process. It encrypted more data (1792 MB) in a small amount of 1240 times per second, and conversations and transactions can be transferred via a secure network to ensure the confidentiality, integrity, and authenticity of users' data. The implementation of such a comprehensive framework in real-life situations can improve chatbot security when it actively works as a customer agent in an organization. [ABSTRACT FROM AUTHOR]

Authenticated encryption with associated data (AEAD) has become prominent over time because it offers authenticity and confidentiality simultaneously. In 2018, the National Institute of Standards and Technology (NIST) initiated a competition to standardize lightweight AEAD and hash functions, with Ascon as the final winner among the 10 finalists. Numerous prior works evaluated their performance on FPGA and ASIC, but not on a parallel architecture like GPU, which is a common accelerator already found in many existing cloud servers. In this work, the first GPU implementation of the NIST AEAD finalists is proposed. Several GPU implementation techniques applicable to all AEAD schemes are presented, along with novel techniques for some specific schemes to enhance throughput performance. Experimental results show that all NIST AEAD finalists can achieve high throughput (up to 111.53M AEAD per second), approximately 142.19% and 72.65% improvement compared to unoptimized GPU version, and the investigated FPGA results respectively. [ABSTRACT FROM AUTHOR]

Verifiable outsourced attribute-based encryption (VO-ABE) enables one-to-many data sharing and fine-grained access control under lower trust, making it suitable for cloud or edge systems involving resource-constrained devices. There is no fully outsourced and fully verifiable attribute-based encryption scheme or key-policy VO-ABE scheme. Moreover, the previous VO-ABE schemes require multiple rounds of interaction or high verification costs to support verifiable outsourced key generation and verifiable outsourced encryption. To address these issues, in this paper, we propose an effective key-policy fully outsourced and fully verifiable attribute-based encryption scheme supporting verifiable outsourced key generation, encryption, and decryption simultaneously. We formally define two new properties: outsourced key generation verifiability and outsourced encryption verifiability. Analysis and simulation show that the proposed scheme performs well and is practical. All local computational overheads of the proposed scheme are constant and do not increase with the number of attributes or the complexity of access structures. [ABSTRACT FROM AUTHOR]

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

Featured Application: Protection and encryption of digital files using hardware fingerprinting. Using an XOR Gate, two Static Random-Access Memory (SRAM) PUFs' challenge–response pairs (CRPs) can be combined into a single larger SRAM PUF. This study focuses on designing enhanced Physically Unclonable Functions (PUFs) based on SRAM devices and improving the security of cryptographic systems. Most SRAM PUFs are limited in their number of CRPs, which makes them vulnerable to enrollment attacks. In this research, we present an SRAM-based PUF design that greatly increases the number of CRPs and the entropy of the generated bits by performing exclusive-or (XOR) on the responses of two SRAM devices. This was implemented using a readily available development board, SRAM devices, and a user-friendly custom circuit board for cryptographic key generation. The cryptographic protocol was implemented using both C++ and python3. The proposed SRAM PUF design was experimentally demonstrated and showed substantial improvements in the security of various cryptographic applications as a hardware authentication device. It also addresses the specific vulnerabilities of legacy designs. [ABSTRACT FROM AUTHOR]

In smart grid systems, the control center formulates strategies and provides services by analyzing electricity consumption data. However, ensuring the privacy and security of user data is a critical concern. While traditional data aggregation schemes can provide a certain level of privacy protection for users, they also impose limitations on the control center's access to fine‐grained data. To address these challenges, we propose a privacy‐preserving data aggregation scheme supporting data query (PAQ). We designed a multi‐level data aggregation mechanism based on Paillier semi‐homomorphic encryption to achieve efficient aggregation of user data in the control center. Additionally, a data query mechanism based on electricity consumption intervals is introduced, allowing the control center to query aggregated ciphertexts for different user categories from outsourced data on the cloud server. Security analysis demonstrates that PAQ design effectively solves security issues in data aggregation and query processes. Performance analysis indicates that the proposed scheme outperforms existing solutions in terms of efficiency. [ABSTRACT FROM AUTHOR]

In distributed computing, data trading mechanisms are essential for ensuring the sharing of data across multiple computing nodes. Nevertheless, they currently encounter considerable obstacles, including low accuracy in matching trading parties, ensuring fairness in transactions, and safeguarding data privacy throughout the trading process. In order to address these issues, we put forward a data trading security scheme based on zero-knowledge proofs and smart contracts. In the phase of preparing the security parameters, the objective is to reduce the complexity of generating non-interactive zero-knowledge proofs and to enhance the efficiency of data trading. In the pre-trading phase, we devise attribute atomic matching smart contracts based on precise data property alignment, with the objective of achieving fine-grained matching of data attributes between trading parties. In the trading execution phase, lightweight cryptographic algorithms based on elliptic curve cryptography (ECC) and non-interactive zero-knowledge proofs are employed for the dual encryption of trading data and the generation of attribute proof contracts, thus ensuring the security and privacy of the data. The results of experiments conducted on the Ethereum platform in an industrial IoT scenario demonstrate that our scheme maintains stable and low-cost consumption while ensuring accuracy in matching and privacy protection. [ABSTRACT FROM AUTHOR]

Storage savings and data confidentiality are two primary goals for outsourced storage. However, encryption by design destroys the content redundancy within plaintext data, so there exist design tensions when combining encryption with data reduction techniques (i.e., deduplication, delta compression, and local compression). We present EDRStore, an outsourced storage system that realizes encrypted data reduction to achieve both storage savings and data confidentiality. EDRStore's core idea is a careful design of the encryption and data reduction workflows. It proposes new key generation and encryption schemes to preserve the content similarity of encrypted data for deduplication and delta compression. It further proposes selective local compression based on content similarity, so as to achieve storage savings of encrypted data from both delta compression and local compression. Evaluation on real-world datasets shows that EDRStore achieves higher storage savings than existing encrypted storage approaches and incurs moderate performance overhead compared with plaintext storage. [ABSTRACT FROM AUTHOR]

This research introduces a novel security framework specifically tailored to enhance data protection during cloud transmission and migration. Our study addresses critical gaps in existing security models by proposing a multi-dimensional system that incorporates advanced encryption techniques, dynamic access control, and continuous security auditing. Notably, this framework excels in ensuring cloud data integrity, confidentiality, and availability--core aspects often compromised under conventional methods. Comparative analysis with existing models in simulated cloud environments reveals that our framework significantly enhances threat detection accuracy, response speed, and resource management efficiency. The findings highlight the system's capability to reduce security vulnerabilities while optimizing operational overhead, presenting a substantial improvement over traditional security solutions. This innovative approach, marked by improved scalability and flexibility, is poised to revolutionize cloud data security practices across various industries, prompting further research into robust cloud computing security methodologies. [ABSTRACT FROM AUTHOR]

The technology-driven modern age emphasizes the security and privacy of communication. Through this paper, we delve deep into the need for user-centric security within cloud-based environments. The need for enhancement in encryption arises due to the increasing cases of data breaches and insider threats in cloud-based environments recently. The focus is laid upon the use of RSA encryption, end-to-end encryption, and anonymous messaging to address security-based concerns. The primary focus of this research is to develop a comprehensive security system to ensure the confidentiality and authenticity of text-based messages shared in the cloud. The proposed improved RSA algorithm, as suggested, incorporates three prime numbers in the key generation process. To address repetitive ciphertext, the proposed algorithm involves adding the index of each character in the plaintext string to the character's integer value before encryption. Conversely, during decryption, the same index is subtracted. This proposed algorithm has been utilized in a practical scenario, specifically in the implementation of a chat application. This paper presents a proof-of-concept for the proposed enhanced version of the RSA algorithm, accompanied by a thorough comparison and analysis of computational times across various bit lengths. Increase in data security at a cost of minor increase in computation time was observed through this research. [ABSTRACT FROM AUTHOR]

Cloud computing enables efficient management and storage of large data volumes, providing scalable resources and effective solutions for handling extensive data. However, the cloud requires attention in the field of data security, reliability and privacy. To ensure that entire data is secured, cloud security handles all devices, apps and data that are integrated into the cloud. To overcome these problems, the encryption of cloud data is an effective way to secure the data. The Elliptic Curve Cryptography (ECC) and Password based Key Derivation Function (PKDF) with Advanced Encryption Standard (AES) method is proposed for effective cloud data security. Initially, the key generation by Edward Elliptic Curve and the key exchange is performed by using Diffie-Hellman Key Exchange (DHKE). Then, keys are generated for the client's password using the PKDF method and the encryption and decryption of data is performed by using the AES method which effectively secures the data in the cloud through encryption and decryption of data. The ECC and PKDF with the AES method require less encryption time of 0.006s and a decryption time of 0.005ms on 5 KB when compared with Hybrid Elliptic Curve Cryptography (HECC). Cloud computing enables efficient management and storage of large data volumes, providing scalable resources and effective solutions for handling extensive datasets. [ABSTRACT FROM AUTHOR]

In studying ample data security in universities, it is essential to protect the privacy and integrity of data. Current schemes utilize blockchain technology for data sharing, where cloud servers are responsible for storing ciphertext and performing partial encryption and decryption calculations. Data encryption technology can effectively prevent hacker attacks and ensure the integrity of data transmission. However, cloud servers that are only partially trusted may tamper with the ciphertext or return incorrect results. To solve these problems, this paper improves the privacy of access policy, attribute revocation and data authenticity of traditional CP-ABE algorithm. A protection scheme for ample public data security in universities is proposed, and a decentralized network structure based on multiple nodes is designed to improve the efficiency of data queries. The simulation results show that the scheme performs well in the scenario where the number of system attributes is moderate and the complexity of the access policy is not high. [ABSTRACT FROM AUTHOR]

A novel polarization‐sensitive artificial optoelectronic synapse based on β‐Ga2O3 single‐crystal is proposed in this work, featuring reconfigurable anisotropic vision. A series of polarization‐sensitive synaptic activities and polarization‐sensitive image recognition functions are successfully simulated using this device. The intriguing performance of this device, stems from the crystal anisotropy in β‐Ga2O3, which is confirmed through polarization Raman measurements and first‐principles theoretical calculations. Furthermore, a comprehensive analysis of the persistent photoelectric properties of the device unveils that the adaptability of the optoelectronic synapse device stems from the ionization and dissociation of oxygen vacancies. Ultimately, the device is utilized in the fields of image recognition and information encryption. A four‐layer artificial neural network with two hidden layers is constructed for recognizing handwritten digits. After training, the recognition accuracy reaches over 91.5% for both unpolarized and polarized light. Information encryption is achieved by controlling polarization states. The device enables data generation and encryption to be conducted on the same platform, mitigating exposure risks during transmission and significantly enhancing data security and confidentiality. This work presents new opportunities for future applications of polarization‐based perception systems. [ABSTRACT FROM AUTHOR]

In the last few years, the volume of internet traffic has increased enormously. A significant portion of the internet traffic is constituted by applications that stream multimedia data from one part of the world to another. The enormity of the video data requires the Content Delivery Network to distribute the content efficiently and securely among the consumers. The secure and authenticated distribution can be achieved by the end-to-end encryption of video. In this paper, one time random key algorithm and the algorithms and methods based on permutation techniques have been proposed to encrypt the video frames selectively and these encrypted frames are transmitted over the network along with the other video frames. The proposed encryption methods extract the colour channels like Red, Green and Blue from the video frames, and they are encrypted by applying row-column permutation cipher, One Time Pad cipher and row permutation cipher. Encryption of the video frames has been performed at two levels by combining the one-time random key algorithm and permutation techniques to provide security to the video. These encryption techniques have been applied on the twenty-five, thirty, and thirty-five, and so on, up to fifty per cent of the total frames available in the video. The experimental results, histogram analysis and parameters like average Peak Signal-to-noise Noise Ratio (PSNR) and Structural Similarity Index (SSIM) values measure the quality of the video obtained after the application of the proposed methods on the video to be transmitted over the network. [ABSTRACT FROM AUTHOR]

Data encryption is an essential building block in modern electronic systems to prevent spying and hacking. Every day more and more objects produce electronic data, and this needs to be encrypted before being transmitted. Hence, designing devices, circuits, and systems for data encryption that can be integrated in all kinds of objects and that consume low amounts of energy is highly necessary. Here, this work reports the fabrication of flexible and transparent electronic circuits consisting of devices that exhibit threshold‐type resistive switching with a high degree of stochasticity. The cycle‐to‐cycle variability of switching voltages and state currents is significant but confined within a well‐defined range, which is consistent across multiple devices. This allows to design an efficient protocol for true random number generation. The circuits are fabricated with only synthetic 2D materials, can be fabricated in a scalable manner, and can be integrated in any object. [ABSTRACT FROM AUTHOR]

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 11.67 Kbps with an overall average execution time of 0.02 s. 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 @ 84 MHz. The proposed encryption method exhibits great features thus making it a potential real-world solution. [ABSTRACT FROM AUTHOR]

Combining the advantages of cryptography and digital watermarking, commutative encryption and watermarking (CEW) addresses the limitations of traditional information security technologies by simultaneously ensuring security and confirming copyright ownership. Existing CEW algorithms for vector geographic data cannot simultaneously meet the requirements of lossless and applicability to all types of vector geographic data. This investigation proposes a lossless CEW algorithm for all types vector geographic data. In the encryption scheme, all coordinate points are stored in a one-dimensional set for permutation encryption. This procedure is applicable to all types of vector geographic data. Then, the original coordinates are replaced with the encrypted coordinates according to the original spatial structure. Since encryption preserves the size of coordinate values, they can be gridded after normalization to ensure compatibility between encryption and watermarking. Subsequently, a characteristic matrix is generated by conducting singular value decomposition on the coordinate values within the grid. Finally, the XOR operation is executed between the encrypted watermark information and this matrix to complete the construction of the zero watermark. Experiments demonstrate that the encryption scheme can yield favorable encryption outcomes with just one scrambling, and the efficiency is greatly improved. The watermarking scheme is robust against most attacks on vector geographic data. [ABSTRACT FROM AUTHOR]

In the 1990s, the US government recognised its citizens required cryptography for protection of digital data but also that encryption may impede law enforcement and intelligence collection. To reconcile these, President Clinton introduced the key-escrow policy, whereby the state would provide citizens with powerful encryption software whilst retaining decryption capabilities. The policy ultimately failed – the determinant reason for its discontinuation is unknown. This article posits and evidences that industry's argument that key-escrow would curtail the global growth of the US technology sector was the determinant factor in the policy's discontinuation. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Many industries are plagued by economic losses and product failures caused by counterfeit goods. Therefore, advanced anti‐counterfeiting techniques are continuously needed. In this study, we constructed a series of acid‐base sensitive cyclic chalcone dyes A—F by modifying different electron‐donating groups. Differences in acid sensitivity of different structures are well rationalised by NMR and theoretical calculations. Aniline is difficult to protonate than fatty amines, so there is a difference in fluorescence. Hiding and anti‐counterfeiting of information is achieved by this phenomenon. Powder X and Y are the anti‐counterfeit fluorescent powder containing montmorillonite and cyclic chalcone, which have orange fluorescence and the very similar appearance. However, under the influence of acid the Powder X containing triphenylamine modified cyclic chalcone shows red shifted fluorescence and Powder Y containing morpholino and diethylamino groups modified cyclic chalcone shows blue shifted fluorescence. Therefore, the anti‐counterfeiting strategy based on cyclic chalcone is not only limited to UV‐irradiated fluorescence development, but also has more colorization and pattern variations with the aid of acid developer. Data encryption and decryption of numbers, English alphabets and Chinese characters have been realized using A—F, which have great potential for practical applications. [ABSTRACT FROM AUTHOR]

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

The global growth of the e-commerce industry has heightened concerns among consumers, businesses, and financial institutions regarding fraud while using credit and debit cards and safeguarding personal information. It is necessary to secure information disseminated over insecure channels to prevent unauthorized access. Cryptography and steganography are widely used for this purpose. However, completely relying on the combined usage of both may not be enough in today's world, resulting in weak security. By combining visual cryptography, more levels of security can be added, thus boosting the security of secret information. This study suggests a data security framework that employs multiple levels of security for information. At the first level of security, cryptography is used to encrypt the secret information, and at the second level of security steganography is used to conceal the encrypted text. After that, visual cryptography is applied, which generates the shares of the image obtained. Finally, image steganography is used to hide the generated shares in different color images. When used together, these data security methods greatly improve the secrecy, trustworthiness, and effectiveness of secret messages. The precision of text is determined through Mean Square Analysis (MSE) and correlation coefficient, which involves a comparison of sent and received text. MATLAB environment is used for the implementation. [ABSTRACT FROM AUTHOR]

Elliptic Curve Cryptography (ECC) and the related cryptographic systems have become widespread alternatives to provide secure channels of communication within our everexpanding networked universe. Cryptosystems play an important role in keeping the privacy of information when it is sent over the network or stored. But as threats and resources grow exponentially higher the only solution is to constantly develop and make more complex systems to remain safe. The Menezes-Vanstone Elliptic Curve Cryptosystem (MVECC) is a cryptographic scheme based on elliptic curve mathematics, designed for data encryption and transmission. A linear Bézier curve is a mathematical construct used in computer graphics, and it's defined by a set of control points. This paper presents an extension to MVECC with a linear Bézier curve equation. This is implemented using a modification of the linear Bézier curve equation to propose the encryption/decryption equations. Also, define a new secret key κ κ , with u (where u ∈ [ 0 , 1 ]) u ∈ [ 0 , 1 ]) and create it with scalar multiplication in ECC by the public key R k R k of MVECC. The purpose of this paper is to enhance the general complexity of the MVECC for key generation, encryption, and decryption operations. This research paper aims to increase the complexity of MVECC by incorporating the behavior of the linear Bézier curve equation. The test of randomness of the ciphertext of the proposed method is depends on several tests issued by the National Institute of Standards and Technology (NIST). The timing of the proposed method has been tested, and the required processes have been calculated. Results show that the proposed modification has the complexity and randomness to provide higher security levels. [ABSTRACT FROM AUTHOR]

The rapid rise of emerging technologies, our daily lives are increasingly shaped by a variety of smart devices. These technologies bring convenience and efficiency, transforming how we live and work. However, they also introduce new challenges, particularly concerning privacy and cybersecurity. As more devices become interconnected through the Internet of Things (IoT), the risk of cyber threats grows, making it essential to address these vulnerabilities. This paper explores the various applications of IoT and examines the potential security risks and privacy concerns that accompany these innovations. [ABSTRACT FROM AUTHOR]

This paper develops the theory of factorial numbers formed by positional number systems with mixed-base factorial number systems. The fundamentals of the theory of factorial numbers are outlined, a method for obtaining them is given, their range is determined, and noise immunity is assessed. The addition and subtraction operations on factorial numbers are considered, and examples of their implementation are given. Methods for transitioning from positional numbers to factorial numbers and back are proposed. Methods are given for converting factorial numbers into permutations and permutations into factorial numbers. The operations of adding and subtracting permutations using factorial numbers are described. The noise immunity of permutations and the ability to detect and correct errors are assessed. The prospects of using permutations formed by factorial numbers for constructing noise-resistant ciphers are shown. [ABSTRACT FROM AUTHOR]

Information security refers to 'the practice of defending information from unauthorised access'. Information security practices include everyday activities such as protecting your bank details, or keeping your workplace logins secure. Despite increasingly restrictive approaches to research ethics, academia continues to lag behind journalism when it comes to best practice with regards to information security. This article discusses information security as it pertains to qualitative and especially ethnographic research into crime and deviance. In doing so, the article addresses a gap in the methodological literature by drawing on lessons and real-world examples from journalism, academia and activism, in order to offer guidance for researchers seeking to maintain information security in a digital, networked social world. The article proceeds in three parts. First, the article considers what information researchers might want to protect, who they might want to protect it from and what the consequences might be if they failed to do so (an exercise known as 'threat modelling'). The different powers, resources and capacities of, and threats posed by, state actors such as the police and intelligence agencies, as well as an array of non-state actors, are considered. Second, the article outlines some general principles of information security and how they might apply to ethnographic research into crime and deviance. Third, the article discusses a range of practical considerations when it comes to using mobile phones (cell phones), social media, passwords and encryption in the course of researching crime and deviance. [ABSTRACT FROM AUTHOR]

In the digital age, the safeguarding of information through effective cybersecurity measures is paramount. This paper presents the development of a robust cryptographic model tailored for cybersecurity applications. The background underscores the increasing prevalence of cyber threats and the necessity for advanced encryption techniques to ensure data confidentiality, integrity, and authenticity. The methodology involves the design and implementation of the cryptographic model using state-of-the-art algorithms and protocols. Rigorous testing and evaluation were conducted to assess the model's performance in various cyber environments. The results indicate that the proposed model significantly enhances security, demonstrating high resistance to common cyber-attacks with an average encryption time of 0.5 seconds for a 1MB file and a decryption accuracy rate of 99.9%. The model also achieved a data integrity verification success rate of 99.8% and an overall system efficiency improvement of 45% compared to existing models. The conclusion highlights the model's effectiveness and potential for broad application in securing digital communication, offering a substantial contribution to the field of cybersecurity. [ABSTRACT FROM AUTHOR]

The health information data includes reports on the patient's condition, including addresses, names, tests, treatments, diagnoses, and medical history. It is sensitive information for patients, and all means of protection must be provided to prevent third parties from manipulation or fraudulent use. It has been discovered that DNA is now a reliable and efficient biological media for securing data. Data encryption is made possible by DNA's bimolecular computing powers. In this paper proposed a new strategy of safeguard the transfer of sensitive data over an unsecured network using cryptography with non-liner function, and DNA lossless compression to enhance security. The work gains best results in compression processes, as percentages range 75%. for character compression, the different rate ranges between 91% to 94%, and the compression rate ranges from 35% to 37%. the retrieving data with an accuracy rate up to 100% without any data loss, as well as excellent percentages within the, Compression Ratio, Compression Factor, Error Rate, Accuracy measures. [ABSTRACT FROM AUTHOR]

With the rapid advancement of cloud computing technology, reversible data hiding algorithms in encrypted images (RDH-EI) have developed into an important field of study concentrated on safeguarding privacy in distributed cloud environments. However, existing algorithms often suffer from low embedding capacities and are inadequate for complex data access scenarios. To address these challenges, this paper proposes a novel reversible data hiding algorithm in encrypted images based on adaptive median edge detection (AMED) and ciphertext-policy attribute-based encryption (CP-ABE). This proposed algorithm enhances the conventional median edge detection (MED) by incorporating dynamic variables to improve pixel prediction accuracy. The carrier image is subsequently reconstructed using the Huffman coding technique. Encrypted image generation is then achieved by encrypting the image based on system user attributes and data access rights, with the hierarchical embedding of the group’s secret data seamlessly integrated during the encryption process using the CP-ABE scheme. Ultimately, the encrypted image is transmitted to the data hider, enabling independent embedding of the secret data and resulting in the creation of the marked encrypted image. This approach allows only the receiver to extract the authorized group’s secret data, thereby enabling fine-grained, controlled access. Test results indicate that, in contrast to current algorithms, the method introduced here considerably improves the embedding rate while preserving lossless image recovery. Specifically, the average maximum embedding rates for the (3, 4)-threshold and (6, 6)-threshold schemes reach 5.7853 bits per pixel (bpp) and 7.7781 bpp, respectively, across the BOSSbase, BOW-2, and USD databases. Furthermore, the algorithm facilitates permission-granting and joint-decryption capabilities. Additionally, this paper conducts a comprehensive examination of the algorithm’s robustness using metrics such as image correlation, information entropy, and number of pixel change rate (NPCR), confirming its high level of security. Overall, the algorithm can be applied in a multi-user and multi-level cloud service environment to realize the secure storage of carrier images and secret data. [ABSTRACT FROM AUTHOR]

Low-resource utilization and high-energy consumption have become progressively protuberant issues in cloud data centers. Virtual Machine (VM) migration is the key objective to resolve this issue. Moreover, extreme VM migration might empower Service-Level Agreement (SLA) violations. Few works are considered for optimizing throughput and energy consumption. An efficient VM migration must consider different parameters like network communication overhead, migration overhead, resource utilization, energy consumption and quality of service which is a multi-objective issue. Hence, in this paper, a Modified Pelican Optimization-based Variable Load Mean Function (MPO-VLMF)-based host overload detection is presented and security enhancement is developed. The main motive of this study is to achieve host overload detection and security enhancement. To obtain host overload detection, the variable load mean function is developed. In this mean function, the weight parameter is selected by considering Modified Pelican Optimization (MPO). The Levy flight (LF) is considered for enhancing the updating process of Pelican Optimization (PO). To enhance the security of the system, the Digital Signature-based Encryption (DSE) is developed. Based on this proposed approach, security and host overload detection are obtained. The proposed technique is implemented and evaluated by performance measures. It is compared with the conventional approaches to justify the performance of the system. [ABSTRACT FROM AUTHOR]

Innovations in wearable technology and artificial intelligence have enabled consumer devices to process and transmit data about human mental states (cognitive, affective, and conative) through what this paper refers to as "cognitive biometrics." Devices such as brain-computer interfaces, extended reality headsets, and fitness wearables offer significant benefits in health, wellness, and entertainment through the collection and processing and cognitive biometric data. However, they also pose unique risks to mental privacy due to their ability to infer sensitive information about individuals. This paper challenges the current approach to protecting individuals through legal protections for "neural data" and advocates for a more expansive legal and industry framework, as recently reflected in the draft UNESCO Recommendation on the Ethics of Neurotechnology, to holistically address both neural and cognitive biometric data. Incorporating this broader and more inclusive approach into legislation and product design can facilitate responsible innovation while safeguarding individuals' mental privacy. Biometric data relating to human cognitive, affective, and conative states ("cognitive biometrics") are not adequately protected under existing privacy laws. The authors argue for an expansive approach that would treat neural and cognitive biometric data holistically as categories of "sensitive data" and provide them with analogous privacy protections. [ABSTRACT FROM AUTHOR]

Photochromic materials are widely used in optical data storage, data encryption, and anti‐counterfeiting because of their ability to be written, erased, and read repeatedly. However, conventional information encryption and storage capabilities based on a "matrix" pattern in a 2D plane are limited to fewer storage dimensions, making information less secure. Here, a new concept of expanding the storage dimensions is presented by manipulating the rotation angle in 2D photochromic encoding disks based on the principle of the absolute encoder. For this purpose, a novel photochromic material, NaNbO3:xEu3+ is developed, with highly efficient red emission, a large luminescence switching contrast, and antithermal quenching behavior. The designed photochromic rotary encoder made with the NaNbO3‐based material exhibits higher‐level data encryption than that of conventional encoders and unlimited storage capability. This study presents exciting opportunities for information storage and encryption using luminescent photochromic materials. [ABSTRACT FROM AUTHOR]

This article examines the foundational principles and protocols that guide the development, implementation and use of encryption and their relevance and impact on technology law and policy. It first focuses on the technical aspects of encryption and explains the meanings of key terms and the different kinds and uses of this technology. It then expounds on the technical principles and protocols of encryption including information security, openness, provable security, and its adversarial nature. The article thereafter analyses the significance and import of these standards and rules on the proposed ghost protocol in encrypted messaging services and encryption law and policy more generally. It argues that technical principles such as information security, primacy of keys and resistance to attacks should be recognised and upheld in the development and adoption of encryption regulation. [ABSTRACT FROM AUTHOR]

Recently, wireless body area network (WBAN) becomes a hot research topic in the advanced healthcare system. The WBAN plays a vital role in monitoring the physiological parameters of the human body with sensors. The sensors are small in size, and it has a small-sized battery with limited life. Hence, the energy is limited in the multi-hop routing process. The patient data is collected by the sensor, and the data are transmitted with high energy consumption. It causes failure in the data transmission path. To avoid this, the data transmission process should be optimized. This paper presents an advanced authentication and energy-efficient routing protocol (AAERP) for optimal routing paths in WBAN. Patients' data are aggregated from the WBAN through the IoMT devices in the initial stage. To secure the patient's private data, a hybrid mechanism of the elliptic curve cryptosystem (ECC) and Paillier cryptosystem is proposed for the data encryption process. Data security is improved by authenticating the data before transmission using an encryption algorithm. Before the routing process, the data encryption approach converts the original plain text data into ciphertext data. This encryption approach assists in avoiding intrusions in the network system. The encrypted data are optimally routed with the help of the teamwork optimization algorithm (TOA) approach. The optimal path selection using this optimization technique improves the effectiveness and robustness of the system. The experimental setup is performed by using Python software. The efficacy of the proposed model is evaluated by solving parameters like network lifetime, network throughput, residual energy, success rate, number of packets received, number of packets sent, and number of packets dropped. The performance of the proposed model is measured by comparing the obtained results with several existing models. [ABSTRACT FROM AUTHOR]

The integration of external devices and network connectivity into autonomous vehicles has raised significant concerns about in-vehicle security vulnerabilities. Existing security mechanisms for in-vehicle bus systems, which mainly rely on appending authentication codes and data encryption, have been extensively studied in the context of CAN and CAN-FD buses. However, these approaches are not directly applicable to Ethernet buses due to the much higher data transmission rates of Ethernet buses compared to other buses. The real-time encryption and decryption required by Ethernet buses cannot be achieved with conventional methods, necessitating an acceleration in the speed of cryptographic operations to match the demands of Ethernet communication. In response to these challenges, our paper introduces a range of cryptographic solutions specifically designed for in-vehicle Ethernet networks. We employ an AES-ECC hybrid algorithm for critical vehicle control signals, combining the efficiency of AES with the security of ECC. For multimedia signals, we propose an improved AES-128 (IAES-128) and an improved MD5 (IMD), which improve encryption time by 15.77%. Our proposed security mechanisms have been rigorously tested through attack simulations on the CANoe (version 10) platform. These tests cover both in-vehicle control signals, such as braking and throttle control, and non-critical systems like multimedia entertainment. The experimental results convincingly demonstrate that our optimized algorithms and security mechanisms ensure the secure and reliable operation of real-time communication in autonomous vehicles. [ABSTRACT FROM AUTHOR]

Recently, cloud computing has become a growing technology in the information technology industry because of its several smooth delivery services. In cloud computing, multi-tenancy is one of the primary features that affords economic and scalability significance to the service providers and end-users by distributing a similar cloud platform. Due to the increasing demand for cloud computing, cloud usage has increased, so various vulnerabilities and threats have also been enhanced. Hence, data security and privacy are considered the major issues of multi-tenant environments in the cloud. Several existing studies have developed different mechanisms to solve security issues in multi-tenant cloud environments. However, they faced various problems while improving security, and this led to a lack of confidentiality, authenticity, and data integrity. Thus, this research paper intends to propose an efficient encryption approach for securing data delivery in the cloud with reduced time. For secure data delivery, homomorphic encryption is utilized to encode the cloud server's data. In homomorphic encryption, four stages are available for data delivery: key generation, encryption, decryption, and evaluation. The main problems in this homomorphic encryption mechanism are key sharing and key management. Due to these problems, the performance of homomorphic encryption is diminished. Thus, the proposed work introduces an Aquila optimizer for the key generation process. In this, optimal keys are selected, and it provides improved data security and privacy for cloud users. Finally, the selected keys are generated for the encryption and decryption process. The efficiency of the proposed approach is proved by comparing the performance in terms of encryption time, decryption time and throughput over the existing schemes like Rivest, Shamir and Adleman, ElGamal, Algebra Homomorphic Encryption scheme based on ElGamal (AHEE) and modified AHEE. The experimental results reveal that the proposed model achieves reduced encryption and decryption time of 972 ms and 4261 ms for the data size ranges from 5 to 25 mb. [ABSTRACT FROM AUTHOR]