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Increasing threat intrusions to enterprise computing systems have led to a formulation of guarded enterprise systems. The approach was to put in place steel gates and prevent hostile entities from entering the enterprise domain. The current complexity level has made the fortress approach to security implemented throughout the defense, banking, and other high trust industries unworkable. The alternative security approach presented in this paper is the result of a concentrated fourteen year program of pilots and research. Its distributed approach has no need for passwords or accounts and derives from a set of tenets that form the basic security model requirements. At each step in the process it determines identities and claims for access and privileges. These techniques are resilient, secure, extensible, and scalable. They are currently being implemented for a major enterprise, and are a candidate for other enterprise security approaches. This paper discusses the Enterprise Level Security architecture, a web-based security architecture designed to select and incorporate technology into a cohesive set of policies and rules for an enterprise information system. The paper discusses the history, theoretical underpinnings, implementation decisions, current status, and future plans for expansion of capabilities and scale.

Network compression coding technology is a research hotspot in the field of digital steganography and image synthesis. How to improve image quality while achieving short compression time is a problem currently faced. Based on the improved wavelet neural network theory, this paper constructs a digital steganography and image synthesis model. The model first tracks the contour of the digit to be recognized, then equalizes and resamples the contour to make it translation-invariant and scaling-invariant, and then uses multi-wavelet neural network clusters to stretch the contour shell to obtain orders of magnitude multi-resolution and its average, and finally, these shell coefficients are fed into a feedforward neural network cluster to identify this handwritten digit, solving the problem of multi-resolution decomposition of contour shells while having a high sampling rate. In the simulation process, the classification model that a single pixel is a text/non-text pixel is trained on the original gray value of the gray pixel and its neighboring pixels, and the classified text pixels are connected to a text area through an adaptive MeanShift method. The experimental results show that it is feasible to use multi-wavelet features for handwritten digit recognition. The model combines the neural network and the genetic algorithm, making full use of the advantages of both, so that the new algorithm has the learning ability and robustness of the neural network. The compression ratio after compression by ordinary wavelet coding, PSNR, MSE, and compression time are 8.4, 25 dB, 210, and 7 s, respectively. The values are 11.7, 24 dB, 207, and 11 s, respectively. At the same time, the peak signal-to-noise ratio is higher and the mean square error is lower, that is, the compression quality is better, and the accuracy of digital steganography and image synthesis is effectively improved. [ABSTRACT FROM AUTHOR]

This is our first IET Information Security special issue from the Internation Conference on Information Security and Cryptology, which was held from December 1 to December 3, Seoul, South Korea, 2021. TOPIC B Paper 3 by K. Yamamura, Y. Wang, and E. Fujisaki investigates an enumeration algorithm that is used as a subroutine for the BKZ algorithm, which is one of the most practical reduction algorithms. [Extracted from the article]

Nowadays, it is difficult to imagine a powerful algorithm of cryptography that can continue cryptanalyzing and attacking without the use of unconventional techniques. Although some of the substitution algorithms are old, such as Vigenere, Alberti, and Trithemius ciphers, they are considered powerful and cannot be broken. In this paper we produce the novelty algorithm, by using of biological computation as an unconventional search tool combined with an uninhibited analysis method is the vertical probabilistic model, that makes attacking and analyzing these ciphers possible and very easy to transform the problem from a complex to a linear one, which is a novelty achievement. The letters of the encoded message are processed in the form of segments of equal length, to report the available hardware components. Each letter codon represents a region of the memory strand, and the letters calculated for it are symbolized within the probabilistic model so that each pair has a triple encoding: the first is given as a memory strand encoding and the others are its complement in the sticker encoding; These encodings differ from one region to another. The solution space is calculated and then the parallel search process begins. Some memory complexities are excluded even though they are within the solution paths formed, because the natural language does not contain its sequences. The precision of the solution and the time consuming of access to it depend on the length of the processed text, and the precision of the solution is often inversely proportional to the speed of access to it. As an average of the time spent to reach the solution, a text with a length of 200 cipher characters needs approximately 15 minutes to give 98% of the correct components of the specific hardware. The aim of the paper is to transform OTP substitution analysis from a NP problem to a O(nm) problem, which makes it easier to find solutions to it easily with the available capabilities and to develop methods that are harnessed to attack difficult and powerful ciphers that differ in class and type from the OTP polyalphabetic substitution ciphers. [ABSTRACT FROM AUTHOR]

Security of linear ramp secret sharing schemes can be characterized by the relative generalized Hamming weights of the involved codes. In this paper, we elaborate on the implication of these parameters and devise a method to estimate their value for general one-point algebraic geometric codes. As it is demonstrated, for Hermitian codes, our bound is often tight. Furthermore, for these codes, the relative generalized Hamming weights are often much larger than the corresponding generalized Hamming weights. [ABSTRACT FROM AUTHOR]

Recently, a robust steganographic algorithm that achieves errorless robustness against JPEG recompression has been proposed. The method employs a lattice embedding scheme and utilizes the syndrome-trellis code (STC) for practical embedding. However, we have noticed that errorless robust embedding with STC may encounter failures due to modifications on wet coefficients, especially when a high quality factor is used by the compression channel. To solve this problem, we have discovered that using steganographic polar code (SPC) for embedding has better performance in avoiding modifications on wet coefficients. In this paper, we conduct theoretical analysis to prove the better performance of SPC in wet paper embedding. We establish the condition of avoiding modifications on wet coefficients, followed by presenting a recursive calculation method for determining the distribution of columns in the generator matrix of SPC. The findings reveal that SPC can avoid modifications on wet coefficients under a larger number of wet coefficients compared with STC, and therefore we propose a better errorless robust embedding method employing SPC. The experimental results demonstrate that under close security performance, the proposed method achieves a higher success rate compared with embedding with STC. Specifically, when the quality factor of the compressor is 95 and the payload size is 0.4 bpnzac, our method achieves a success rate of 99.85%, surpassing the 91.95% success rate of the embedding with STC. [ABSTRACT FROM AUTHOR]

Priced oblivious transfer (POT) is a cryptographic protocol designed for privacy-preserving e-commerce of digital content. It involves two parties: the merchant, who provides a set of priced items as input, and a customer, who acquires one of them. After the protocol has run, the customer obtains the item they chose, while the merchant cannot determine which one. Moreover, the protocol guarantees that the customer gets the content only if they have paid the price established by the merchant. In a recent paper, the authors proposed a POT system where the payments employed e-coin transactions. The strong point of the proposal was the absence of zero-knowledge proofs required in preceding systems to guarantee the correctness of payments. In this paper, we propose a novel e-coin-based POT system with a fast item retrieval procedure whose running time does not depend on the number of items for sale. This is an improvement over the aforementioned existing proposal whose execution time becomes prohibitively long when the catalog is extensive. The use of zero-knowledge proofs is neither required. [ABSTRACT FROM AUTHOR]

The security of public key cryptography relies on the complexity of certain mathematical hard problems. It is vital to comprehend the intricacy of these problems to develop secure cryptographic schemes and security protocols. This paper provides an overview of some widely recognized hard problems associated with the discrete logarithm problem, including the reductions among them. Furthermore, we introduce a novel hard problem that is equivalent to the discrete logarithm problem, which also has a decisional version. Additionally, a set of new problems is presented, which can be instrumental in the design of secure encryption schemes. This paper is intended to provide crucial insights into the realm of hard problems in cryptography, facilitating a better understanding of security measures. [ABSTRACT FROM AUTHOR]

In the paper entitled "Spam Detection Approach for Secure Mobile Message Communication Using Machine Learning Algorithms", L. G. Jun et al. proposed the applications of the machine learning-based spam detection method for accurate detection. The data extraction process of the review showed that (1) latent Dirichlet allocation topic modeling is among the widely used machine learning algorithms in the selected studies and (2) precision and recall are amongst the most utilized evaluation methods for measuring the performance of these machine learning algorithms. Machine learning (ML) and cryptography have many things in common, for instance, the amount of data to be handled and large search spaces. [Extracted from the article]

With the rapid development of wireless communication technology, positioning technology, and modern smart devices, Internet of Vehicles (IoVs) smart vehicles have brought great convenience to human production and life. Meanwhile, privacy and security issues are becoming extremely serious, with serious consequences if sensitive data such as vehicle location and trip patterns are leaked. This paper focuses on the demands for vehicular network security, especially privacy protection and existing privacy-protection techniques, including common cryptography methods and cryptography-based advanced technologies. At the same time, this paper also analyzes the advantages and challenges of these technologies in protecting privacy and network security in the Internet of Vehicles, such as the challenges of computational resource requirements and security efficiency in the implementation process, as well as the complexity of realizing effective privacy protection in the interactions among different entities. Finally, this paper envisions the development of privacy-preserving application scenarios and the prospects for crypotography-based privacy-preserving technologies. [ABSTRACT FROM AUTHOR]

In this paper, we study the permutation properties of the class of trinomials of the form f(x) = x4q+1 + λ1xq+4 + λ2x2q+3 ∈ Fq²[x] where λ1, λ2 ∈ Fq and they are not simultaneously zero. We find all necessary and sufficient conditions on λ1 and λ2 such that f(x) permutes Fq², where q is odd and q = 22k+1, k ∈ N. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach to enhancing multi-level security using steganography, a method of concealing information within non-secret data. This paper introduces an innovative approach to multi-level security enhancement using steganography, the art of concealing information within non-obvious data. Our proposed method uniquely combines Dynamic Least Significant Bit (DLSB) steganography with Wavelet Obtained Weights (WOW) steganographic algorithms, forging a sophisticated and adaptable system for secret data embedding. In our enhanced approach, we start by embedding text into an image using an optimized version of DLSB steganography. This refined technique adapts intelligently to the image's local contrast, thereby preserving its visual quality and ensuring the integrity of the embedded information. Subsequently, the payload image is merged with a cover image through the WOW algorithm. This step optimally selects pixels for data embedding, creating a steganographic image that is virtually indistinguishable from the original. The novelty of our work lies in the seamless integration of these two advanced steganographic techniques, which significantly elevates the security and invisibility aspects beyond the current state-of-the-art methods in digital steganography. For validation, we utilized a pretrained MobileNet model to differentiate between original and stego images. This model plays a crucial role in demonstrating the indetectability of our method, achieving an impressive accuracy of 85% in distinguishing stego images from their originals. Our rigorous testing across various metrics — including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Bit Error Rate (BER), and Mean Squared Error (MSE) — showcases the effectiveness of our approach. The results indicate a robust performance, marking a significant advancement in secure digital communication. In this paper, we focus primarily on the detailed presentation of our results and the significant contributions of our current research, setting a strong foundation for future exploration in increasing robustness against steganalysis and improving the statistical invisibility of the steganography process. [ABSTRACT FROM AUTHOR]

In the realm of smart communication systems, where the ubiquity of 5G/6G networks and IoT applications demands robust data confidentiality, the cryptographic integrity of block and stream cipher mechanisms plays a pivotal role. This paper focuses on the enhancement of cryptographic strength in these systems through an innovative approach to generating substitution boxes (S-boxes), which are integral in achieving confusion and diffusion properties in substitution–permutation networks. These properties are critical in thwarting statistical, differential, linear, and other forms of cryptanalysis, and are equally vital in pseudorandom number generation and cryptographic hashing algorithms. The paper addresses the challenge of rapidly producing random S-boxes with desired cryptographic attributes, a task notably arduous given the complexity of existing generation algorithms. We delve into the hill climbing algorithm, exploring various cost functions and their impact on computational complexity for generating S-boxes with a target nonlinearity of 104. Our contribution lies in proposing a new cost function that markedly reduces the generation complexity, bringing down the iteration count to under 50,000 for achieving the desired S-box. This advancement is particularly significant in the context of smart communication environments, where the balance between security and performance is paramount. [ABSTRACT FROM AUTHOR]

As the global data strategy deepens and data elements accelerate integrating and flowing more rapidly, the demand for data security and privacy protection has become increasingly prominent. Confidential computing emerges as a crucial security technology to solve security and privacy problem, and it is also a hot subject of in contemporary security technologies. Leveraging collaborative security in both hardware and software, it builds a trusted execution environment to ensure confidentiality and integrity protection for data in use. This paper provides a comprehensive overview of the development process of confidential computing, summarizing its current research status and issues, which focuses on the security requirements for data security and privacy protection. Furthermore, it deeply analyses the common technical features of confidential computing, and proposes a trusted confidential computing architecture based on collaborative hardware and software trust. Then, it elaborates on the research status and issues of confidential computing from four aspects: hardware security, architecture and key technologies, applications, and standards and evaluation. Finally, this paper provides a synthesis and outlook for the future development of confidential computing. In summary, confidential computing is currently in a rapidly developing stage and will play an important role in cyber security in the future. [ABSTRACT FROM AUTHOR]

Cloud computing is an online data storage system that can be easily accessed anywhere. Various algorithms and techniques have been developed to secure cloud data, which, if used correctly, can detect cloud attacks. These algorithms can only detect cloud data attacks and cannot prevent such attacks. If an attacker gains access to the data, he or she can tamper with the data in any way that could lead to misuse of the data. This paper will design a secure architecture for securing data with various algorithm implementations on the architecture so that cloud data can be saved from replay attacks. First, a text file will be taken, the text file will be encrypted using the encryption mechanism, and this file will be transmitted on the SaaS cloud server platform. Whenever a file is uploaded to a cloud server, it will be broadcast across the network, after which any user can access it, whether it is valid or invalid. Whenever a file is downloaded from a cloud server, it will be necessary to decrypt it to access it. If the file is successfully decrypted, then the file will be verified. A verification mechanism will be used to verify the data, which will be used to check whether a replay attack has been made on the data or not. If the data authentication is successful, this data will be called authentic data. The novelty of this paper is that an algorithm has been developed in this paper to prevent replay attacks so that if the data is retransmitted with slight changes, then the authenticity and inauthenticity of the data will be identified. Recent papers will be compared with the proposed paper in the conclusion, and it will be pointed out how much better the current technique is than the previous one. [ABSTRACT FROM AUTHOR]

We study the application of Hamming codes to wet paper steganography. To that end, we propose the use of decoding algorithms that do not verify the minimum distance property and present one of these algorithms. We study its properties and show results of some numerical experiments. [ABSTRACT FROM AUTHOR]

This paper explores and elucidates the concept of Cryptocurrency. It contributes a framework of digital money and also provides an analysis of the price range, which influences Cryptocurrency volume and market capitalisation. Findings from the OLS analysis show that the low price genre influences the volume and market capitalization of Cryptocurreny. Based on the results, the paper develops a price, volume and market capitalization framework for Cryptocurrency. The findings provide a practical and conceptual contribution for investors and future researchers on the concept of digital currency. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence (AI), deep learning is widely used in various industries. At CRYPTO 2019, researchers used deep learning to analyze the block cipher for the first time and constructed a differential neural network distinguisher to meet a certain accuracy. In this paper, a mixture differential neural network distinguisher using ResNet is proposed to further improve the accuracy by exploring the mixture differential properties. Experiments are conducted on SIMON32/64, and the accuracy of the 8-round mixture differential neural network distinguisher is improved from 74.7% to 92.3%, compared with that of the previous differential neural network distinguisher. The prediction accuracy of the differential neural network distinguisher is susceptible to the choice of the specified input differentials, whereas the mixture differential neural network distinguisher is less affected by the input difference and has greater robustness. Furthermore, by combining the probabilistic expansion of rounds and the neutral bit, the obtained mixture differential neural network distinguisher is extended to 11 rounds, which can realize the 12-round actual key recovery attack on SIMON32/64. With an appropriate increase in the time complexity and data complexity, the key recovery accuracy of the mixture differential neural network distinguisher can be improved to 55% as compared to 52% of the differential neural network distinguisher. The mixture differential neural network distinguisher proposed in this paper can also be applied to other lightweight block ciphers. [ABSTRACT FROM AUTHOR]

Mainstream research on information theory within the field of living systems involves the application of analytical tools to understand a broad range of life processes. This paper is dedicated to an opposite problem: it explores the information theory and communication engineering methods that have counterparts in the data transmission process by way of DNA structures and neural fibers. Considering the requirements of modern multimedia, transmission methods chosen by nature may be different, suboptimal, or even far from optimal. However, nature is known for rational resource usage, so its methods have a significant advantage: they are proven to be sustainable. Perhaps understanding the engineering aspects of methods of nature can inspire a design of alternative green, stable, and low-cost transmission. [ABSTRACT FROM AUTHOR]

Video steganography has the potential to be used to convey illegal information, and video steganalysis is a vital tool to detect the presence of this illicit act. Currently, all the motion vector (MV)‐based video steganalysis algorithms extract feature sets directly from the MVs, but ignoring the embedding operation may perturb the statistical distribution of other video encoding elements, such as the skipped macroblocks (no direct MVs). This paper proposes a novel 11‐dimensional feature set to detect MV‐based video steganography based on the above observation. The proposed feature is extracted based on the skipped macroblocks by recompression calibration. Specifically, the feature consists of two components. The first is the probability distribution of motion vector prediction (MVP) difference, and the second is the probability distribution of partition state transfer. Extensive experiments on different conditions demonstrate that the proposed feature set achieves good detection accuracy, especially in lower embedding capacities. In addition, the loss of detection performance caused by recompression calibration using mismatched quantization parameters (QP) is within the acceptable range, so the proposed method can be used in practical scenarios. [ABSTRACT FROM AUTHOR]

Cryptology is a part of mathematics as encryption and decryption. The purpose of encryption is to make information incomprehensible when it is in the hands of unauthorized people. The receiver can decrypt the message that encrypted by the sender with helping of the key. The important point is that the key cannot be decrypted by other people. One Time Pad method solves this problem. The key is used only once each encryption in this method. So, the key becomes harder to guess. If the key is solved by unauthorized people, the message cannot be solved. Because of with each decryption, many meaningful messages are obtained. Every cyclic shift in a cyclic code constructs a new key and in each encryption is used the new key. Many keys are generated thanks to cyclic codes. In this paper, we improve the new encryption scheme by using the cyclic codes with One Time Pad method. [ABSTRACT FROM AUTHOR]

The fast advance and evolution of technology in Internet of Things (IoT) is a double-edged sword, striking with new performant solutions and backfiring with a lot of unanswered questions. Due to cheap manufacturing costs and large-scale production, sensors, actuators and even microcontrollers are not designed with security on the first place. Also, the IoT market is a new one and that means that it is still unregulated and there isn’t a well-defined set of standards to control and manage better these problems. The IoT ascent has impacted many industries, but probably the most changes were made to the Supply Chain Management (SCM) industry. The forementioned question of cheap devices that need to be manufactured with a minimum of costs, very fast and ready to be deployed, is digging a big security hole in this kind of ecosystems. This paper aims to discuss the challenges involved in hardening de security in embedded devices, protecting the data and the communication channels between an IoT node and an IoT gateway and finally, assuring the persistence of data and its security after is stored. All these matters are addressed with privacy and security in design. Because SCM is a multiparty ecosystem that involves many different actors each with its tasks and data handling components, it is important to assure the fact that they will not interfere, tamper, or profit in a bad manner of each other. One solution for this problem is decentralization that comes with strings attached. Finally, and on short, this paper will try to describe a security model based on decentralization in a SCM flow, addressing its threats and how they can be overcome. [ABSTRACT FROM AUTHOR]

In recent years, reversible logic gates have garnered significant interest because of their potential to decrease energy consumption and meet the growing need for low-power computing systems. Unlike conventional logic gates, reversible logic gates ensure that no information loss happens during computation, allowing for the reversal of the entire computation process. This unique characteristic opens up new avenues for developing energy-efficient digital circuits. This review paper serves as a vital contribution to the field by addressing a noticeable gap in the existing literature regarding reversible logic gates. The study not only comprehensively analyzes the array of reversible logic gates available but also underscores their practical applications and significance. It encompasses a wide variety of reversible logic gates, including Toffoli gates, Fredkin gates, and newer innovations. It is found that Toffoli gates outperformed in terms of gate count and quantum cost reduction, making them a preferred choice for quantum circuit optimization. Additionally, Fredkin gates showed exceptional performance in specific applications, like data swapping and quantum state control. The digital circuits like adders, multiplexers, ALU etc. are successfully designed using reversible gates like HNG, DKG etc. The significant gap this study fills lies in the need for a consolidated and in-depth analysis of the state-of-the-art reversible logic gates and their real-world utility. While prior research has discussed these gates individually, this paper takes a novel approach by offering a holistic assessment of their performance, quantum cost, gate count, and practical applications, thereby presenting a comprehensive resource for researchers, engineers, and designers in the field. This innovative contribution plays a pivotal role in shaping the progress of energy-efficient and quantum computing systems as well as in optimizing VLSI chip designs for various applications, with a particular emphasis on enhancing cryptographic and data processing capabilities. The findings of this review aim to stimulate further research and development in reversible computing, contributing to the advancement of energy-efficient and information-preserving computing systems. [ABSTRACT FROM AUTHOR]

Conditional Privacy Preserving Authentication (CPPA) schemes are an effective way of securing communications in vehicular ad hoc networks (VANETs), as well as ensuring user privacy and accountability. Cryptanalysis plays a crucial role in pointing out the vulnerabilities in existing schemes to enable the development of more resilient ones. In 2019, Zhang proposed a CPPA scheme for VANET security (PA-CRT), based on identity batch verification (IBV) and Chinese Remainder Theorem (CRT). In this paper, we cryptanalyze Zhang's scheme and point out its vulnerability to impersonation and repudiation attacks. In 2023, Zhang's scheme was cryptanalyzed by Tao; however, we point out flaws in Tao's cryptanalysis due to invalid assumptions; hence, we propose countermeasures to Tao's attacks. Furthermore, in 2021, Xiong proposed a Certificateless Aggregate Signature (CLAS) scheme which is also cryptanalyzed in this paper. Finally, we analyze the causes and countermeasures by pointing out the vulnerabilities in each scheme that enabled us to launch successful attacks and proposing changes that would fortify these schemes against similar attacks in the future. [ABSTRACT FROM AUTHOR]

Context and background: The blockchain technology is as a new technology in vogue that is virtually getting a swift application in most important art world transactions. This is due to its public distributed, transparent, accountable, traceable and safe, ledger database, also is the advantage to secure a successful transaction without a third party. As the world keeps growing in the knowledge and the adoption of the technology, it is very important to practically explore the opportunities in this technology to combat the security and copyright problems facing land ownership transactions in the Cadastre system. Goal and Objectives: The goal of this paper is to practically access the possibility of engaging the blockchain technology in land administration and ownership systems while the objective is to convert legal instrument(s) into cryptographic readable data. Methodology: This was done by minting survey plans template into Non-Fungible Token. Two blockchains (Solana and CORE blockchains) were considered to show the possibility of adopting the technology in land administration and ownership systems. The selection was based on their flexibility, Scalability and the potentials to solve the trilemma blockchain problems. A survey plan template called DEMO (no real) was created for this purpose. Transactions on the FONE network Art NFT marketplace built on Solana blockchain was examined while an art NFT of survey plan template was minted on the Youngparrot NFT marketplace built on CORE blockchain. Results: The transactions were completed and the survey plan was successfully minted on the Core blockchain. the minting and transaction records are available and can be traced on the public blockchain ledger. Due to this advantage, this paper urges the consideration to take advantage of the possibilities and positivity of the technology in Land Administration sector and land ownership system and also provides steps to achieving its successful adoption. In addition, this is not a financial advice but a research work. [ABSTRACT FROM AUTHOR]

This paper intends to contribute to the emerging literature on the ethical problems posed by quantum computing and quantum technologies in general. The key ethical questions are as follows: Does quantum computing pose new ethical problems, or are those raised by quantum computing just a different version of the same ethical problems raised by other technologies, such as nanotechnologies, nuclear plants, or cloud computing? In other words, what is new in quantum computing from an ethical point of view? The paper aims to answer these two questions by (a) developing an analysis of the existing literature on the ethical and social aspects of quantum computing and (b) identifying and analyzing the main ethical problems posed by quantum computing. The conclusion is that quantum computing poses completely new ethical issues that require new conceptual tools and methods. [ABSTRACT FROM AUTHOR]

To solve for these problems, various schemes providing the perfect/unconditional security have been proposed, including physical-layer security (PLS), quantum key distribution (QKD), and post-quantum cryptography. Authors introduce the unambiguous state discrimination measurement and the photon-number-splitting attack against PM-QKD with imperfect phase randomization, demonstrating the rigorous security of decoy state PM-QKD with a discrete-phase randomization protocol. The topics addressed in this Special Issue include physical-layer security [[2]], quantum key distribution (QKD) [[2]], post-quantum cryptography [[6]], quantum-enhanced cryptography [[7]], stealth communication [[2]], and covert communication [[8]]. In the third article paper [[13]], authors introduce an open-destination MDI QKD network that provides security against untrusted relays and all detector side-channel attacks, in which all user users are capable of distributing keys with the help of other users. [Extracted from the article]

Cloud cryptography is the art of converting plain text into an unreadable format, which protects data and prevents the data from being misused by the attacker. Different researchers designed various Caesar cipher algorithms for data security. With the help of these algorithms, the data can be converted into a nonreadable format, but the data cannot be completely secured. In this paper, data security is provided in different phases. Firstly, data are secured through a bit-reversing mechanism in which those replace the actual values with no relation to the original data. Then the four-bit values are added at the beginning and end of bits using a salting mechanism to interlink the salting and existing bit-values and hide the original data. A Caesar cipher value is obtained by applying the Caesar cipher algorithm to the resulting bits. The Caesar cipher algorithm is used to implement number-of-shifting on the obtained values. An efficient cipher matrix algorithm is then developed in which different rules are designed to encrypt the data. Afterward, a secure cipher value is obtained by implementing Cipher XORation rules on the result obtained and the user-defined key. In the end, the proposed algorithm is compared with various papers. It identifies how much better the proposed algorithm performs than all the previous algorithms and how much the attack rate can be reduced if this algorithm is used for data security. [ABSTRACT FROM AUTHOR]

Graph representation learning has made significant strides in various fields, including sociology and biology, in recent years. However, the majority of research has focused on static graphs, neglecting the temporality and continuity of edges in dynamic graphs. Furthermore, dynamic data are vulnerable to various security threats, such as data privacy breaches and confidentiality attacks. To tackle this issue, the present paper proposes a data security detection method based on a continuous-time graph embedding framework (CTDGE). The framework models temporal dependencies and embeds data using a graph representation learning method. A machine learning algorithm is then employed to classify and predict the embedded data to detect if it is secure or not. Experimental results show that this method performs well in data security detection, surpassing several dynamic graph embedding methods by 5% in terms of AUC metrics. Furthermore, the proposed framework outperforms other dynamic baseline methods in the node classification task of large-scale graphs containing 4321477 temporal information edges, resulting in a 10% improvement in the F1 score metric. The framework is also robust and scalable for application in various data security domains. This work is important for promoting the use of continuous-time graph embedding framework in the field of data security. [ABSTRACT FROM AUTHOR]

Digital signature technology is essential for ensuring the authenticity and unforgeability of transactions in a private blockchain framework. In some scenarios, transactions require verification from multiple parties, each of whom needs to authenticate different parts of the transaction. To address this issue, researchers have developed multi-party ECDSA (Elliptic Curve Digital Signature Algorithm) signature schemes. However, these schemes either need to consider the authentication of different parts of the transaction or generate an aggregated signature. This paper proposes a novel solution that combines functional signatures and multi-party ECDSA signatures to create a multi-party functional signature for private blockchains. Compared to previous constructions, the proposed scheme ensures that each part of the transaction is verified. Furthermore, when the aggregate signature of the entire transaction cannot be verified, this scheme identifies the specific part of the transaction for which the signature authentication fails instead of rejecting the entire transaction. This paper uses a smart contract to securely deploy the proposed scheme and authenticate the f in functional signatures. The constructed scheme also provides security under the existential unforgeability of the ECDSA signature, even if n − 1 parties are corrupted, assuming a total of n parties. The scheme of this paper successfully conducted experiments on a personal computer, with three users taking approximately 343 ms, six users taking 552 ms, and nine users taking 791 ms. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a technological paradigm that has gained significant momentum the last decade and, among other features, enables the development of intelligent and interoperable device networks. In this respect, it has triggered the creation and evolution of vehicular ad-hoc networks (VANETs), which are initially implemented in order to guarantee the safety of drivers and the avoidance of traffic accidents. The drawback is that this fast evolution comes with serious concerns in terms of the privacy of users, while the population of attackers or entities that try to eavesdrop and intercept information has significantly increased. This imposes a serious risk for drivers moving across a Smart City. The research presented in this paper aims to evaluate privacy protection mechanisms in VANET environments, based on the efficiency and security level they ensure, considering the fact that VANETs provide limited resources to users/drivers. Moreover, the usage of elliptic curve cryptography in reduced resources environments is discussed. Finally, this paper compares the performance of three cryptographic algorithms, elliptic curve cryptography (ECC), hyperelliptic curve cryptography genus 2 (HECC-2) and HECC genus 3 (HECC-3), employed for an efficient authentication and safe message transmission mechanism in VANETs, aimed at reaching conclusions related to the implementation of each cryptographic scheme in this specific application area. The evaluation results indicate that ECC supersedes HECC-2 and HECC-3 in most metrics. However, HECC-2 and HECC-3 demonstrate better responses than ECC does in selected energy metrics. Overall, it is observed that HECC algorithms are not yet mature enough to compete with ECC. This is due to the fact that the research community has not sufficiently progressed toward the optimization of HECC, and moreover, HECC builds on quite complex mathematics. There are indications, however, that once HECC curves are indeed optimized, HECC will outperform ECC in speed as well as in other metrics, sinceHECC-2 and HECC-3 use a significantly smaller key size with the same level of security as that of ECC. [ABSTRACT FROM AUTHOR]