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This paper presents a statistical analysis of the enhanced SDEx (Secure Data Exchange) encryption method, using a version that incorporates two session keys. This method has not previously been combined with the BLAKE3 hash function. The statistical analysis was conducted using the NIST Statistical Test Suite. Several real-world sample files were encrypted using the proposed method and then subjected to statistical analysis through selected tests from the NIST suite. These tests aimed to determine whether the resulting ciphertexts meet the criteria for pseudorandomness. Additionally, compression tests were performed using WinRAR, which confirmed that the ciphertexts are not compressible.

The paper presents analysis of the possibility of using selected hash functions submitted for the SHA-3 competition in the SDEx encryption method. The group of these functions will include the finalists of the SHA-3 competition, i.e. BLAKE, Grøstl, JH, Keccak, Skein. The aim of the analysis is to develop more secure and faster cryptographic algorithm compared to the current version of the SDEx method with SHA- 512 and the AES algorithm. When considering the speed of algorithms, mainly the software implementation will be taken into account, as it is the most commonly used.

Electronic Health Records (EHR) serve as a solid documentation of health transactions and as a vital resource of information for healthcare stakeholders. EHR integrity and security issues, however, continue to be intractable. Blockchain-based EHR architectures, however, address the issues of integrity very effectively. In this work, we suggest a decentralized patient-centered healthcare data management (PCHDM) with a blockchain-based EHR framework to address issues of confidentiality, access control, and privacy of record. This patient-centric architecture keeps the patient at the center of control for secured storage of EHR data. It is effective in the storage environment with the interplanetary file system (IPFS) and blockchain technology. In order to control unauthorized users, the proposed secure password authentication-based key exchange (SPAKE) implements smart contract-based access control to EHR transactions and access policies. The experimental setup comprises four hyperledger fabric nodes with level DB database and IPFS off-chain storage. The framework was evaluated using the public hepatitis dataset, with parameters such as block creation time, transactional computational overhead with encryption key size, and uploading/downloading time with EHR size. The framework enables patient-centric access control of the EHR with the SPAKE encryption algorithm.

Intending to enable a broader collaboration with the scientific community while maintaining privacy of the data stored and generated in Living Labs, this paper presents the Shareable Data Publishing and Access Service for Living Labs, implemented within the framework of the H2020 VITALISE project. Building upon previous work, significant enhancements and improvements are presented in the architecture enabling Living Labs to securely publish collected data in an internal and isolated node for external use. External researchers can access a portal to discover and download shareable data versions (anonymised or synthetic data) derived from the data stored across different Living Labs that they can use to develop, test, and debug their processing scripts locally, adhering to legal and ethical data handling practices. Subsequently, they may request remote execution of the same algorithms against the real internal data in Living Lab nodes, comparing the outcomes with those obtained using shareable data. The paper details the architecture, data flows, technical details and validation of the service with real-world usage examples, demonstrating its efficacy in promoting data-driven research in digital health while preserving privacy. The presented service can be used as an intermediary between Living Labs and external researchers for secure data exchange and to accelerate research on data analytics paradigms in digital health, ensuring compliance with data protection laws.

Blockchain and deep reinforcement learning (DRL) are two separate transaction systems committed to the credibility and usefulness of system functionality. There is rapid growth importance in integrating both technologies into effective and stable information exchange and research solutions. Blockchain is a revolutionary platform for future generational telecommunications networking that will set up the secured and distributed information exchange framework. In combination with DRL, blockchain could significantly improve the efficiency of mobile communications. The rapid growth of networks for the Internet of Things (IoT) necessitates the development of suitable and reliable infrastructure as well as a significant proportion of the information. Blockchain, a distributed and reliable ledger, is often considered a considerably beneficial means of providing scientific confidentiality and security to IoT devices. When interacting with massive IoT records, the Blockchain’s decrease becomes a significant issue. Thus, it is necessary to improve transaction performance and deal with massive data transmission situations. As a result, the work presented here explores the DRL fundamental operation of the blockchain-enabled IoT system, where transactions are simultaneously strengthened, and community-based divisibility is ensured. Throughout this paper, the authors first present the decentralised and efficient structure for communication by incorporating DRL and blockchain across wireless services that allow for the scalable and reliable allocation of information. The results show that the proposed method has shorter delays and requires less transmission power.

Virtual reality (VR)/the metaverse is transforming into a ubiquitous technology by leveraging smart devices to provide highly immersive experiences at an affordable price. Cryptographically securing such augmented reality schemes is of paramount importance. Securely transferring the same secret key, i.e., obfuscated, between several parties is the main issue with symmetric cryptography, the workhorse of modern cryptography, because of its ease of use and quick speed. Typically, asymmetric cryptography establishes a shared secret between parties, after which the switch to symmetric encryption can be made. However, several SoTA (State-of-The-Art) security research schemes lack flexibility and scalability for industrial Internet-of-Things (IoT)-sized applications. In this paper, we present the full architecture of the PRIVocular framework. PRIVocular (i.e., PRIV(acy)-ocular) is a VR-ready hardware–software integrated system that is capable of visually transmitting user data over three versatile modes of encapsulation, encrypted—without loss of generality—using an asymmetric-key cryptosystem. These operation modes can be optical character-based or QR-tag-based. Encryption and decryption primarily depend on each mode’s success ratio of correct encoding and decoding. We investigate the most efficient means of ocular (encrypted) data transfer by considering several designs and contributing to each framework component. Our pre-prototyped framework can provide such privacy preservation (namely virtual proof of privacy (VPP)) and visually secure data transfer promptly (<1000 ms), as well as the physical distance of the smart glasses (∼50 cm).

Modern distributed computing systems and applications with strict privacy requirements demand robust data confidentiality. A primary challenge involves enabling parties to exchange data or perform joint computations. These interactions must avoid revealing private information about the data. Protocols with the obliviousness property, known as oblivious protocols, address this issue. They ensure that no party learns more than necessary. This survey analyzes the security and performance of post-quantum oblivious protocols, with a focus on oblivious transfer and oblivious pseudorandom functions. The evaluation assesses resilience against malicious adversaries in the Universal Composability framework. Efficiency is quantified through communication and computational overhead. It identifies optimal scenarios for these protocols. This paper also surveys related primitives, such as oblivious signatures and data structures, along with their applications. Key findings highlight the inherent trade-offs between computational cost and communication complexity in post-quantum oblivious constructions. Open challenges and future research directions are outlined. Emphasis is placed on quantum-resistant designs and formal security proofs in stronger adversarial models.

Let us consider a situation where two information brokers, whose currency is, of course, information, need to reciprocally exchange information. The two brokers, being somewhat distrustful, would like a third, mutually trusted entity to be involved in the exchange process so as to guarantee the successful completion of the transaction and also verify that it indeed took place. Can this be completed in such a way that both brokers receive their information simultaneously and securely, without the trusted intermediary knowing the exchanged information? This work presents and rigorously analyzes a new quantum entanglement-based protocol that provides a solution to the above problem. The proposed protocol is aptly named the entanglement-based reciprocal simultaneous information exchange protocol. Its security is ultimately based on the assumption of the existence of a third, trusted party. Although the reciprocal information flow is between our two information brokers, the third entity plays a crucial role in mediating this process by being a guarantor and a verifier. The phenomenon of quantum entanglement is the cornerstone of this protocol, as it makes its implementation possible even when all entities are spatially separated and ensures that, upon completion, the trusted third party remains oblivious to the actual information that was exchanged.

Signcryption is a highly efficient approach to simultaneously achieving message confidentiality and authentication in Human-Centered IoT (HC-IoT) systems. HCIoT is a new field of study that links various aspects of life such as smart cards, business, e-commerce, healthcare, and sensitive private data. A number of intelligent systems favor human intervention to start automated tasks. A number of smart devices have a social effect in that they should be capable of changing their functional model based on the behavior of different humans. It has boosted the development of information exchange over the IoT and enabled networks. It encompasses cellular, vehicular, and human healthcare by utilizing middleware. Currently, group signcryption schemes are gaining widespread popularity in HC-IoT environments. HC-IoT is useful in electronic cash systems, lightweight devices, multi-server networks, and more. However, most signcryption schemes use bilinear pairing that is computationally intensive, and there is a need for more efficient signcryption schemes. In order to solve this issue, this paper introduces an efficient Certificateless Group-oriented Signcryption (CGS) scheme using Quantum Chebyshev Chaotic Maps (QCCM) without employing bilinear pairing. The proposed QCCM-CGS scheme’s standout feature is that any group signcrypter can signcrypt a text/information with the group manager (GM) and then present it to the verifier for verification. By using the public conditions of the group, the verifier approves the validity of the signcrypted text and cannot connect the signcrypted text to the conforming signcrypter. However, a legitimate signcrypted text cannot be generated even by the GM or any signcrypter of that group unaccompanied. In situations where there is a legal disagreement, such as non-repudiation of the signature, the GM can reveal the identity of the signcrypter. The presented scheme is adequately secured from the indistinguishably chosen ciphertext attack. The computationally challenging problem, QCCM, is used as the foundation for the construction of traceability, unforgeability, unlinkability, and security. Lastly, the security review of the projected scheme clearly shows significant consistency, and it can be easily deployed in vulnerable security applications.

Today’s digital world necessitates the adoption of encryption techniques to ensure secure peer-to-peer communication. The sole purpose of this paper is to conglomerate the fundamentals of Blockchain, AI (Artificial Intelligence) and DNA (Deoxyribonucleic Acid) encryption into one proposed scheme, KryptosChain, which is capable of providing a secure information exchange between a sender and his intended receiver. The scheme firstly suggests a DNA-based Huffman coding scheme, which alternatively allocates purines—Adenine (A) and Guanine (G), and pyrimidines—Thymine (T) and Cytosine (C) values, while following the complementary rule to higher and lower branches of the resultant Huffman tree. Inculcation of DNA concepts makes the Huffman coding scheme eight times stronger than the traditional counterpart based on binary—0 and 1 values. After the ciphertext is obtained, the proposed methodology next provides a Blockchain-inspired message exchange scheme that achieves all the principles of security and proves to be immune to common cryptographic attacks even without the deployment of any smart contract, or possessing any cryptocurrency or arriving at any consensus. Lastly, different classifiers were engaged to check the intrusion detection capability of KryptosChain on the NSL-KDD dataset and AI fundamentals. The detailed analysis of the proposed KryptosChain validates its capacity to fulfill its security goals and stands immune to cryptographic attacks. The intrusion possibility curbing concludes that the J84 classifier provides the highest accuracy of 95.84% among several others as discussed in the paper.