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With current advancement in hybermedia knowledges, the privacy of digital information has developed a critical problem. To overawed the susceptibilities of present security protocols, scholars tend to focus mainly on efforts on alternation of current protocols. Over past decade, various proposed encoding models have been shown insecurity, leading to main threats against significant data. Utilizing the suitable encryption model is very vital means of guard against various such, but algorithm is selected based on the dependency of data which need to be secured. Moreover, testing potentiality of the security assessment one by one to identify the best choice can take a vital time for processing. For faster and precisive identification of assessment algorithm, we suggest a security phase exposure model for cipher encryption technique by invoking Support Vector Machine (SVM). In this work, we form a dataset using usual security components like contrast, homogeneity. To overcome the uncertainty in analysing the security and lack of ability of processing data to a risk assessment mechanism. To overcome with such complications, this paper proposes an assessment model for security issues using fuzzy evidential reasoning (ER) approaches. Significantly, the model can be utilised to process and assemble risk assessment data on various aspects in systematic ways. To estimate the performance of our framework, we have various analyses like, recall, F1 score and accuracy. [ABSTRACT FROM AUTHOR]

This article provides a general overview of the communication protocols used in the IEC61850 standard for the automation of electrical substations. Specifically, it examines the GOOSE and R-GOOSE protocols, which are used for exchanging various types of information. The article then presents real cases of cyber attacks on the industrial sector, highlighting the importance of addressing cybersecurity in the IEC61850 standard. The text presents security drawbacks of the communication protocols mentioned earlier and briefly explains two algorithms defined in the IEC61850 standard to address them. However, the authors suggest that having only a couple of algorithms may not be sufficient to ensure digital security in substations. This article presents a study on the cryptographic algorithms ChaCha20 and Poly1305. The purpose of the study is to experimentally verify their adaptation to the strict time requirements that GOOSE must meet for their operation. These algorithms can operate independently or in combination, creating an Authenticated Encryption with Associated Data (AEAD) algorithm. Both algorithms were thoroughly reviewed and tested using GOOSE and R-GOOSE frames generated by the S-GoSV software. The computational time required was also observed. The frames were analysed using the Wireshark software. It was concluded that the algorithms are suitable for the communication requirements of electrical substations and can be used as an alternative to the cryptographic algorithms proposed under the IEC61850 standard. [ABSTRACT FROM AUTHOR]

Joint image compression and encryption algorithms are intensively investigated due to their powerful capability of simultaneous image data compression and sensitive information protection. Unfortunately, most of the existing algorithms suffered from either poor compression efficiency or weak encryption strength, making them vulnerable to cryptanalysis. To address these limitations, we propose a chaos-based JPEG-compatible joint image compression and encryption algorithm. We separate the luminance and chrominance coefficients to preserve file size and encrypt the discrete cosine transform (DCT) coefficients in parallel. The proposed inter-block DC encryption strategy achieves high encryption intensity based on the permutation-substitution structure. In addition, we apply both inter- and intra-block permutations to AC coefficients and strengthen the encryption using an inter-block substitution for non-zero AC coefficients. The results of security and performance analyses demonstrate that the proposed algorithm offers robust encryption of image data while maintaining compression efficiency for real-time transmission. [ABSTRACT FROM AUTHOR]

In the era of rapid technological advancement, the proper adaptation of legal frameworks and secure technologies is crucial to ensure legal certainty in land ownership. The National Land Agency (Badan Pertanahan Nasional or ATR/BPN) plays a central role in managing the issuance of electronic land certificates. This research aims to investigate the role of electronic land certificates in providing legal protection in Indonesia and analyze the challenges and vulnerabilities that arise with the development of information technology. Employing a normative legal method, this study focuses on the analysis of norms and legal regulations governing the use of electronic land certificates in the land registration system. The research approach includes a legislative approach, a conceptual approach, and the use of primary and secondary legal materials. The results emphasize the importance of careful adaptation to information technology developments to maintain legal certainty in land ownership, highlighting the central role of the ATR/BPN and the necessity of appropriate regulations, data security, legal validity, technical requirements, and technology utilization, including data encryption and network security measures, to address vulnerabilities. Adequate awareness and training are also deemed essential for all stakeholders involved. [ABSTRACT FROM AUTHOR]

This paper proposes a solution to the problem of software absence for the quantitative fire safety analysis of complex objects, which is suitable not only for highly qualified scientists and experts but also for fire safety engineers and inspectors and is compatible with mobile devices. Existing software solutions for quantitative fire safety analysis are desktop-based, and all require a high level of competence of users. We propose a solution by combining the formalism of typical probabilistic structural–logical (TPSL) models, the Software-as-a-Service (SaaS) concept, and end-to-end encryption. Using TPSL models allows the development of cloud-based applications with a simple request-based application programming interface and intuitively understandable user interface to assess the level of safety of complex objects. As a result, we could use such mobile device-ready applications both for developing mobile device applications and developing mobile-device-friendly website-based services to carry out safety control inspections or level of safety management. [ABSTRACT FROM AUTHOR]

In virtual power plants, diverse business scenarios involving user data, such as queries, transactions, and sharing, pose significant privacy risks. Traditional attribute-based encryption (ABE) methods, while supporting fine-grained access, fall short of fully protecting user privacy as they require attribute input, leading to potential data leaks. Addressing these limitations, our research introduces a novel privacy protection scheme using zero-knowledge proof and distributed attribute-based encryption (DABE). This method innovatively employs Merkel trees for aggregating user attributes and constructing commitments for zero-knowledge proof verification, ensuring that user attributes and access policies remain confidential. Our solution not only enhances privacy but also fortifies security against man-in-the-middle and replay attacks, offering attribute indistinguishability and tamper resistance. A comparative performance analysis demonstrates that our approach outperforms existing methods in efficiency, reducing time, cost, and space requirements. These advancements mark a significant step forward in ensuring robust user privacy and data security in virtual power plants. [ABSTRACT FROM AUTHOR]

Summary: Image encryption is crucial for protecting image privacy and ensuring security. Encrypting large batches of images of different types and sizes simultaneously with losslessly decryption is often necessary. This paper proposes an optical asymmetric multi-image encryption algorithm to meet these demands. First, plaintext images are converted into one-dimensional pixels and blocked. Image information, image count, and pixels are stored in corresponding areas and reassembled. Unit equal-modulus vector decomposition (UEMD) and phase truncation generate the ciphertext image and keys. The decrypted image is reconstructed from the ciphertext’s information and quantity areas. Asymmetric encryption with different keys for encryption and decryption enhances security, while UEMD ensures lossless recovery and robustness. Experiments demonstrate the proposed algorithm’s efficiency in encrypting multiple grayscale and color images of varying sizes, providing high security, and lossless recovery. This technology offers superior protection for sensitive image data, enhancing encryption system practicality and digital security.

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

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

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

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]

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]

Introduction: Internet of things (IoT) compose of million of devices connected together over the internet. IoT plays a vital role now a days and especially in future, the most of the monitoring and data collection. The data should be secure while collection and as well in the process of transferring till the destination whether Service Organization Control (SOC) or to cloud for storage. In this paper, a secure IoT based intelligent monitoring system is proposed. Methods: An intelligent IoT station that interacts via cellular connection to relay data to the cloud is constructed using the Waspmote platform. The algorithm is injected to automatically filter and only keep the new data for transfer to avoid redundancy. The advanced encryption standard (AES) 256-bit method is enabled for onboard data encryption and then the generated cipher text is transmitted. The encrypted data is then stored over the cloud to ensure privacy. Moreover, the mobile application (mApp) is developed to be installed on handheld devices for calling the secure data from the cloud, decrypting it, and displaying it as per user input, whether real-time or historical. Results and Discussion: The encryption algortihm helps in securing the proposed monitoring system from brute force, man in the middle, phishing, spoofing, and denial of service (DoS) attacks. The results of the real testbed experimentation demonstrate the complexity evaluation and reliability of IoT monitoring systems with end-to-end data security in terms of encryption algorithm delay and data rate, respectively. [ABSTRACT FROM AUTHOR]

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

Long-lived thermally activated delayed fluorescence (TADF) emission has gained extensive attention due to its potential application in information encryption, illumination, and bioimaging. However, developing visible light-excited TADF materials is still a significant challenge. Herein, visible light triggered TADF emission was achieved by embedding chlorine doped carbon dots (Cl-CDs) into a g-C3N4 nanosheet matrix through a simple microwave treatment. The strong electron-withdrawing effect of the chlorine dropping redshifts the excitation wavelength, and the covalent bonds between Cl-CDs and the matrix significantly stabilize the triplet state. Green TADF with a peak at 520 nm could be obtained in the Cl-CD composite when excited by the UV to visible light, and the afterglow signal can be observed by the naked eye for up to 5 s after a mobile phone flashlight irradiation. The composite also exhibited temperature-responsive color stability under UV light irradiation. Consequently, the Cl-CD composite was successfully employed in concepts of information encryption and single-component time delay WLED development. This research provides materials and strategies that may motivate the visible light-excited TADF applied in advanced information encryption and illumination areas. [ABSTRACT FROM AUTHOR]

A sweeping computational ghost imaging (SCGI)-based encryption system is intended for increased data security and speedier data transport. SCGI is combined with steganography and cryptography processes in this system. SCGI requires fewer shots, resulting in faster image capture, transmission, encryption, and decryption. This strategy also results in smaller, more compact data packages and higher bitrates. Least significant bit (LSB) uses steganography to conceal the hidden picture. In the case of Rivest-Shamir-Adleman (RSA) encryption, public and private keys are generated via a one-way function based on bucket values. Encryption is performed on two levels, with an asymmetric approach divided into three sub-items that significantly increase encryption. Surprisingly, the method uses fewer pictures for image reconstruction, resulting in faster image reconstruction. SCGI promises applications in an extensive number of data encryption sectors since this technology leads to smaller data packages and higher bitrates. The presented approach is examined using the number of pixel change rate (NPCR), normalized root mean square (NRMS), peak signal-to-noise ratio (PSNR), and correlation coefficient (CC), which indicates constant encryption improvement. We experimentally and situationally demonstrate our findings under eavesdropping, which prove the resistance and robustness of our methods. In optimal settings, this innovation enhances encryption by up to 90% when compared to traditional encryption methods. [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]

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

The security of patient data is a critical problem for health networks due to the rising popularity of telehealth services and the requirements for clinical data sharing between surgeons, consultants, and medical groups. In contrast to protecting medical data, which includes the cover (i.e., clinical picture), the requirements for protecting other pertinent data are more general. The paper advocates for data encryption before concealment as a robust strategy to uphold patient privacy during medical information exchange. The primary focus of this analysis revolves around a comprehensive exploration of different steganography methods. Through a meticulous examination of various steganographic techniques, including LSB, PVD, and transform domain approaches, this paper provides a detailed analysis of their strengths and limitations. Objective metrics like PSNR and SSIM are employed to dissect the trade-offs between data security and visual fidelity. The research leads to the conclusion that the diagonal queue-based steganog-raphy methodology, supported by chaotic methods, the Linear Feedback Shift Register (LFSR), and the durable Rabin encryption system, is the best course of action. This method enables autonomous data transmission among numerous contacts while ensuring the highest level of confidentiality and integrity of patient data inside e-health networks. In summary, this study provides a comprehensive solution that protects patient data and speeds data transmission inside the expanding framework of e-health networks in order to meet urgent data security concerns in telemedicine and healthcare data exchange. [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]

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]

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]

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]

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

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

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]

The Internet of Things (IoT) is a revolutionary paradigm that has gained significant prominence in recent years. It represents the interconnection of everyday objects, devices and machines to the internet, allowing them to collect, exchange and analyze data. As the number of connected objects grows exponentially, energy consumption and data security become essential challenges to ensure a sustainable development of green IoT. Data compression theory can be used as an enticing key to downsize the large amount of circulated information, since wireless communication is the prime energy consuming component in IoT devices. In addition, data encryption algorithms are crucial to protect sensitive information and ensure the integrity and confidentiality of IoT systems. Therefore, combining compression and encryption can lead to improved overall IoT system performance in terms of both power cost and data privacy. In this paper, a lightweight and secure compression approach is introduced to efficiently manage the energy expenditure and provide end-to-end security for energy constrained devices. This proposed algorithm combines the performance of LTC compression and AES encryption to securely encode collected data in IoT devices. The energy model analysis has shown that the suggested method is effective in terms of processing energy, reduces the volume of transmitted data and guarantees end-to-end information privacy. [ABSTRACT FROM AUTHOR]

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

Metasurface holography has aroused immense interest in producing holographic images with high quality, higher-order diffraction-free, and large viewing angles by using a planar artificial sheet consisting of subwavelength nanostructures. Despite remarkable progress, dynamically tunable metasurface holography in the visible band has rarely been reported due to limited available tuning methods. In this work, we propose and numerically demonstrate a thermally tunable vanadium dioxide (VO2) nanofin based binary-phase metasurface, which generates holographic information in the visible varying with temperature. The insulator-to-metal phase transition in VO2 nanofins allows two independent binary-phase holograms generated by machine learning to be encoded in the respective phases of VO2 and switched under thermal regulation. By elaborately designing the dimensions and compensated phase of VO2 nanofins, high-quality images are reconstructed at corresponding temperatures under appropriate chiral illumination. In contrast, much poorer images are produced under inappropriate chiral illumination. We further demonstrate the advantage of applying the VO2 phase-compensated metasurface in high-security digital encryption, where two desired character combinations are read out with appropriate excitations and temperatures, whereas one identical fraudulent message is received with inappropriate excitations. Our design approach offers a new and efficient method to realize tunable metasurfaces, which is promisingly adopted in dynamic display, information encryption, optical anti-counterfeiting, etc. [ABSTRACT FROM AUTHOR]

Advances in nanophotonics have created numerous pathways for light–matter interactions in nanometer scale, enriched by physical and chemical mechanisms. Over the avenue, electrically tunable photonic response is highly desired for optical encryption, optical switch, and structural color display. However, the perceived obstacle, which lies in the energy-efficient tuning mechanism and/or its weak light–matter interaction, is treated as a barrier. Here, we introduce electrochromic nanopixels made of hybrid nanowires integrated with polyaniline (PANI). The device shows optical duality between two resonators: (i) surface plasmon polariton (SPP)-induced waveguide (wavelength-selective absorber) and (ii) ultrathin resonator (broadband absorber). With switching effect of between resonant modes, we achieve enhanced chromatic variation spanning from red to green and blue while operating at a sub-1-volt level, ensuring compatibility with the CMOS voltage range. This modulation is achieved by improving the light–matter interaction, effectively harnessing the intrinsic optical property transition of PANI from lossy to dielectric in response to the redox states. In our experimental approach, we successfully scaled up device fabrication to an 8-inch wafer, tailoring the nanowire array to different dimensions for optical information encryption. Demonstrating distinct chromaticity modulation, we achieve optical encryption of multiple data bits, up to 8 bits per unit cell. By capitalizing on the remarkable sensitivity to the angular dependence of the waveguiding mode, we further enhance the information capacity to an impressive 10 bits per unit cell. [ABSTRACT FROM AUTHOR]

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

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

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

In this paper, we design a lightweight and modified random key generation for PRESENT block cipher which is applicable in the encryption of the digital signals. In the block ciphers, the master key is used directly in the encryption process for the data (plaintext). But in this work, a master key (initial key) is used to derive the new random master keys (random session keys) and use these keys for the encryption process. The use of random keys will overcome the brute force attack that can be applied to the PRESENT cipher. The random session keys generated will produce different ciphertexts for the same plaintext for every session. In this approach, we take advantage of the block cipher to produce random keys. The PRESENT cipher is shared in both random key generation and encryption process. Therefore, the proposed structure has both random key generation and data encryption in a unified circuit. This property reduces hardware resources. The implementation results, in 180 nm CMOS technologies, show the proposed structure is comparable in terms of area and delay with other works. [ABSTRACT FROM AUTHOR]

Hybrid encryption techniques are gaining popularity in the cloud platform due to their ability to address security concerns and data storage challenges. In order to ensure confidentiality at every stage of processing, this article presents an innovative strategy that merges fully homomorphic encryption (FHE) and secure hash algorithm 3 (SHA-3), offering robust protection against cyber threats. FHE and SHA-3 offer a solution to this problem. We conducted experiments using different datasets to test the performance and security strength of this hybrid approach. Our method takes into account factors such as computational overheads, complexity requirements, key management challenges, and limited support from vendors/providers offering specialized hardware/software capable of supporting complex mathematical functions required by each technique separately before combined into a hybrid form suitable enough scaled-out horizontally across different nodes within clouds themselves today globally among end-users relying upon them heavily day-to-day tasks involving mission-critical workloads running inside virtualized machines hosted on public/private clouds ecosystems worldwide. The results show that implementing FHE together with SHA-3 can significantly improve an organization's overall cyber security posture when operating critical infrastructure components residing within cloud environments. According to the results, it performs better than other methods that are currently in used complexity of encryption and decoding, including homomorphic encryption and RSA, AES & DSA, and AES & RSA. The hybrid algorithm we are proposed using fully homomorphic & SHA3 with 2048 bits 0.789 seconds of encryption time and decryption time with 0.001 seconds and execution time with 4.25 seconds. Therefore, we conclude that our proposed hybrid encryption technique is the best approach to address cyber security risks associated with storing sensitive data in cloud computing environments. [ABSTRACT FROM AUTHOR]

Audio cryptography is the practice of encrypting audio data to prevent illegal access to and listening to it. This paper presents an innovative technique of audio cryptography based on the Python computer language. To ensure secrecy and integrity, the suggested system encrypts and decrypts audio signals using advanced cryptographic techniques. A crucial component of AES, the cryptographic key is dynamically created to improve security. Python's broad library support and ease of use make it an ideal platform for implementing the AES algorithm, which ensures dependable and effective audio data encryption. The system utilizes Python's cryptography library for seamless integration and ease of implementation. Simulation results demonstrate the efficacy of the AES algorithm in securely encrypting and decrypting audio data with reduced noise compared to traditional methods. [ABSTRACT FROM AUTHOR]

With the rapid development of information technology, huge data information is exchanged every moment in various types of networks, which contain information such as commercial secrets and personal privacy, and data security has a great impact on people's lives. To address the issues of low efficiency and poor security in network link transmission layer database security encryption systems, a new system is studied and designed to strengthen the protection of data information from both hardware and software aspects. Then, a discrete chaotic system is introduced to ensure the stability of the dynamic grouping encryption algorithm. Finally, trajectory loop rotation is used to obtain address clusters using the discrete chaotic system, and dual address loop rotation is used to achieve the variability of the dynamic grouping algorithm. The experiment shows that for different file sizes, the encryption speed of the Dynamic Packet Encryption Optimization (DPEO) algorithm is stable between 5.84 and 5.98 mb/s. And after minor changes in the key, the NPCR of the ciphertext obtained by the DPEO algorithm exceeds 99.5%. In addition, its operation efficiency is excellent, reaching the stable entropy value in only 0. 52 s. In summary, the DPEO algorithm in the network link transport layer database security encryption system can combine high efficiency and excellent security performance. [ABSTRACT FROM AUTHOR]

BIM collaborative design involves numerous participants from various specialties who create and share vast amounts of design data at different design stages to ensure the efficient transmission of design data between these specialties. It is imperative for the BIM collaborative design platform to guarantee the security of design data and effectively trace any instances of malicious leakage or tampering. Therefore, this paper proposes a traceable ciphertext-policy attribute-based encryption scheme (TCP-ABE) that formulates a dynamic data access control mechanism based on different participants and effectively tracks malicious users in the event of risks such as tampering, theft, and unauthorized access to BIM data. In this scheme, the user's identity information is embedded into their private key as a key component, ensuring that only users who satisfy the access policy can decrypt it. The compromised private key allows for tracing of the user's identity. Additionally, Linear Secret Sharing Scheme (LSSS) is employed as the access structure with the user's attribute set divided into an attribute name set and an attribute value set to protect privacy by concealing the latter within the access policy. Furthermore, the scheme integrates blockchain with cloud storage as a trusted third-party storage mechanism to ensure data integrity. Finally, the TCP-ABE scheme is comprehensively evaluated by comparing its strengths and weaknesses with other algorithms. This evaluation includes a theoretical analysis of functional and computational time overhead aspects, as well as an experimental analysis of initialization time, data encryption time, and data decryption time. The scheme exhibits excellent performance across all stages and encompasses the most comprehensive functionalities, as demonstrated by the comparative analysis and experimental results. [ABSTRACT FROM AUTHOR]

An advanced electronic information equipment interface control and status monitoring system is proposed to ensure the fairness, objectivity, and security of information while identifying responsibility for traffic accidents. Through an in-depth analysis of the system's security requirements and the current landscape of information security technology, a robust security strategy is developed for each crucial system stage. A PC-based platform is developed for efficient data acquisition, secure processing, reliable transmission, and fortified storage, focusing on implementing nonlinear data encryption methods. Performance evaluation of the system involved rigorous testing using files ranging from 3MB to 10MB. The results of the proposed system revealed a significant improvement in the system's overall speed and efficiency, showcasing an average performance enhancement of one quarter compared to the original platform. The proposed system demonstrated an impressive 15% to 30% increase in processing speed, establishing its capability to ensure data integrity protection during information transmission, facilitate accurate identification of data recording equipment post-accident, and safeguard the security of stored data. The developed electronic information equipment interface control and status monitoring system effectively addresses critical challenges associated with ensuring data integrity and security in traffic accident investigations. [ABSTRACT FROM AUTHOR]

Copyright of Jordanian Journal of Computers & Information Technology is the property of Jordanian Journal of Computers & Information Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In a cloud environment, outsourced graph data is widely used in companies, enterprises, medical institutions, and so on. Data owners and users can save costs and improve efficiency by storing large amounts of graph data on cloud servers. Servers on cloud platforms usually have some subjective or objective attacks, which make the outsourced graph data in an insecure state. The issue of privacy data protection has become an important obstacle to data sharing and usage. How to query outsourcing graph data safely and effectively has become the focus of research. Adjacency query is a basic and frequently used operation in graph, and it will effectively promote the query range and query ability if multi-keyword fuzzy search can be supported at the same time. This work proposes to protect the privacy information of outsourcing graph data by encryption, mainly studies the problem of multi-keyword fuzzy adjacency query, and puts forward a solution. In our scheme, we use the Bloom filter and encryption mechanism to build a secure index and query token, and adjacency queries are implemented through indexes and query tokens on the cloud server. Our proposed scheme is proved by formal analysis, and the performance and effectiveness of the scheme are illustrated by experimental analysis. The research results of this work will provide solid theoretical and technical support for the further popularization and application of encrypted graph data processing technology. [ABSTRACT FROM AUTHOR]

6G is envisioned as the next generation of wireless communication technology, promising unprecedented data speeds, ultra-low Latency, and ubiquitous Connectivity. In tandem with these advancements, blockchain technology is leveraged to enhance computer vision applications' security, trustworthiness, and transparency. With the widespread use of mobile devices equipped with cameras, the ability to capture and recognize Chinese characters in natural scenes has become increasingly important. Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount, such as facial recognition or personal healthcare monitoring. Users can control their visual data and grant or revoke access as needed. Recognizing Chinese characters from images can provide convenience in various aspects of people's lives. However, traditional Chinese character text recognition methods often need higher accuracy, leading to recognition failures or incorrect character identification. In contrast, computer vision technologies have significantly improved image recognition accuracy. This paper proposed a Secure end-to-end recognition system (SE2ERS) for Chinese characters in natural scenes based on convolutional neural networks (CNN) using 6G technology. The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph (WHCC) of the secure data transmission in the 6G network with the blockchain model. The data transmission within the computer vision system, with a 6G gradient directional histogram (GDH), is employed for character estimation. With the deployment of WHCC and GDH in the constructed SE2ERS model, secure communication is achieved for the data transmission with the 6G network. The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication. Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88% for simple Chinese characters, compared to 81.2% with traditional methods. For complex Chinese characters, the average recognition accuracy improves to 84.4% with our system, compared to 72.8% with traditional methods. Additionally, deploying the WHCC model improves data security with the increased data encryption rate complexity of ~12 & higher than the traditional techniques. [ABSTRACT FROM AUTHOR]

Ensuring the protection of digital data is of utmost importance in our current reliance on network operations. However, security measures such as data encryption often result in decreased performance speed. This paper enhanced the 128-bit version of the advanced encryption standard (AES) by substituting the MixColumns function with a permutation-based approach and decreasing the overall number of rounds. The evaluation results indicate a substantial enhancement in the speed of encryption and decryption, with a 76.76% improvement in encryption time and a 55.46% improvement in decryption time. Furthermore, it is important to mention that the modifications implemented in the standard AES did not compromise its security in relation to the strict avalanche criterion. The avalanche effect of the modified AES is 52.92%, surpassing the minimum requirement of 50%. Finally, the modified AES demonstrated a 31.12% increase in throughput for encryption and a 25.50% increase for decryption when compared to the original AES, using the sample dataset. [ABSTRACT FROM AUTHOR]

Data sharing is increasingly important across various industries. However, issues such as data integrity verification during sharing, encryption key leakage, and difficulty sharing data between different user groups have been identified. To address these challenges, this study proposes a multi-group data sharing network model based on Consortium Blockchain and IPFS for P2P sharing. This model uses a dynamic key encryption algorithm to provide secure data sharing, avoiding the problems associated with existing data transmission techniques such as key cracking or data leakage due to low security and reliability. Additionally, the model establishes an IPFS network for users within the group, allowing for the generation of data probes to verify data integrity, and the use of the Fabric network to record log information and probe data related to data operations and encryption. Data owners retain full control over access to their data to ensure privacy and security. The experimental results show that the system proposed in this study has wide applicability. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xinjiang University (Natural Science Edition) is the property of Xinjiang University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article informs about the challenges of data interoperability in global healthcare systems, emphasizing the impact of poor EHR deployments on patient safety and healthcare quality. Topics include the prevalence of EHR-related patient safety issues, the importance of standards-based approaches to minimize interoperability risks, and the role of health information exchanges in facilitating comprehensive patient medical histories.

The need of data owners for privacy protection has given rise to collaborative learning, and data-related issues heterogeneity faced by federated learning has further given rise to clustered federated learning; whereas the traditional privacy-preserving scheme of federated learning using homomorphic encryption alone fails to fulfill the privacy protection demands of clustered federated learning. To address these issues, this research provides an effective and safeguarded answer for sharing homomorphic encryption keys among clusters in clustered federated learning grounded in conditional representative broadcast re-encryption. This method constructs a key sharing mechanism. By combining the functions of the bilinear pairwise accumulator and specific conditional proxy broadcast re-ciphering, the mechanism can verify the integrity of homomorphic encryption keys stored on cloud servers. In addition, the solution enables key management centers to grant secure and controlled access to re-encrypted homomorphic encryption keys to third parties without disclosing the sensitive information contained therein. The scheme achieves this by implementing a sophisticated access tree-based mechanism that enables the cloud server to convert forwarded ciphertexts into completely new ciphertexts customized specifically for a given group of users. By effectively utilizing conditional restrictions, the scheme achieves fine-grained access control to protect the privacy of shared content. Finally, this paper showcases the scheme's security against selective ciphertext attacks without relying on random prediction. [ABSTRACT FROM AUTHOR]

In this paper, we propose a three-dimensional (3D) optical encryption technique for simultaneous two-primary data using double random-phase encryption (DRPE). In conventional DRPE, the primary data can be encrypted through two different random phase masks optically. Thus, its speed is the same as the speed of light. However, in this method, each primary dataset can be decrypted by the individual key data. For simultaneous two primary dataset such as stereo images or multi-view images, a new encryption technique is required. Therefore, in this paper, we encrypt the simultaneous two different primary datasets by DRPE. In our method, the first and second primary data are regarded as the amplitude and phase with single key data for encryption. To verify the feasibility of our method, we implement the simulation and measure the performance metrics such as thw peak signal to noise ratio (PSNR) and the peak sidelobe ratio (PSR). As a result, PSNR values of two-dimensional decryption results for the first ("LENA" text) and second (lena image) primary data by our proposed method with the correct and incorrect key data are 311.0139, 41.9609, 12.0166, and 7.4626, respectively, since the first primary data are lossless, and the second primary data are lossy. For 3D reconstruction, PSR values of the first and second primary data are 914.2644 and 774.1400, respectively. [ABSTRACT FROM AUTHOR]

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

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