Explore the vast range of titles available.

Telemedicine diagnosis has become a more flexible and convenient way to receive diagnoses, which is of great significance in enhancing diagnosis, cutting costs, and serving remote users. However, telemedicine faces many security problems, such as the complexity of user authentication, the balance of the existing biometric factor authentication scheme, the unpredictability of user behavior, and the difficulty of unified authentication due to the differences in the security standards and authentication mechanisms of different trust domains, which affect the sustainable development of telemedicine. To address the above issues, this paper presents an identity management scheme based on multi-factor authentication and dynamic trust evaluation for telemedicine. Its authentication combines iris recognition for secure biometric verification, smart cards for encrypted credential storage, and static passwords for supplementary verification, addressing scenarios like facial coverage in medical settings. The scheme dynamically adjusts authentication based on attack rates, login anomalies, and service durations. By integrating ShangMi cryptographic algorithms and blockchain, it optimizes performance, achieving 35% lower communication overhead than previous protocols. A security analysis shows it resists impersonation, man-in-the-middle, and password modification attacks while preserving user anonymity. System evaluation meets authoritative standards, validating its practicality. This scheme balances security and efficiency, providing a strong basis for telemedicine’s long-term viability.

A blockchain, or in other words a chain of transaction blocks, is a distributed database that maintains an ordered chain of blocks that reliably connect the information contained in them. Copies of chain blocks are usually stored on multiple computers and synchronized in accordance with the rules of building a chain of blocks, which provides secure and change-resistant storage of information. To build linked lists of blocks hashing is used. Hashing is a special cryptographic primitive that provides one-way, resistance to collisions and search for prototypes computation of hash value (hash or message digest). In this paper a comparative analysis of the performance of hashing algorithms that can be used in modern decentralized blockchain networks are conducted. Specifically, the hash performance on different desktop systems, the number of cycles per byte (Cycles/byte), the amount of hashed message per second (MB/s) and the hash rate (KHash/s) are investigated. The comparative analysis of different hashing algorithms allows us to choose the most suitable candidates for building decentralized systems type of blockchain.

In the evolving landscape of global trade digitalization, port supply chains play a pivotal role as critical components of international logistics. These supply chains face pressing needs to enhance the efficiency and security of warehouse receipt management. Traditional methods often grapple with challenges such as information isolation, vulnerabilities in data security, and suboptimal collaboration efficiency. This paper introduces a novel cross-chain warehouse receipt management system that leverages a notary mechanism and ShangMi (SM) cryptographic algorithms to overcome these obstacles. The system is structured around an innovative “3 + 1” multi-chain architecture, which consists of three distinct business chains—production, port, and sales—and a cross-chain management platform that orchestrates communication between these chains. The proposed system employs a layered data structure for warehouse receipts and uses differentiated encryption strategies. These features enable flexible data sharing while ensuring the protection of sensitive information. To further enhance operational efficiency, the system incorporates performance optimization strategies such as batch processing and incremental synchronization. Experimental evaluations reveal significant performance improvements over conventional systems. For instance, under conditions of 800 concurrent users, our system achieves a query latency of 485.3 milliseconds (ms) compared to 7,900 ms in the reference system, and maintains a query throughput of 565.4 transactions per second (TPS), in stark contrast to approximately 100TPS in the reference system. These results underscore the technical superiority of our approach in practical business scenarios.

Background: The technological revolution has allowed users to exchange data and information in various fields, and this is one of the most prevalent uses of computer technologies. However, in a world where third parties are capable of collecting, stealing, and destroying information without authorization, cryptography remains the primary tool that assists users in keeping their information secure using various techniques. Blowfish is an encryption process that is modest, protected, and proficient, with the size of the message and the key size affecting its performance. Aim: the goal of this study is to design a modified Blowfish algorithm by changing the structure of the F function to encrypt and decrypt video data. After which, the performance of the normal and modified Blowfish algorithm will be obtained in terms of time complexity and the avalanche effect. Methods: To compare the encryption time and security, the modified Blowfish algorithm will use only two S-boxes in the F function instead of the four used in Blowfish. Encryption and decryption times were calculated to compare Blowfish to the modified Blowfish algorithm, with the findings indicating that the modified Blowfish algorithm performs better. Results: The Avalanche Effect results reveal that normal Blowfish has a higher security level for all categories of video file size than the modified Blowfish algorithm, with 50.7176% for normal Blowfish and 43.3398% for the modified Blowfish algorithm of 187 kb; hence, it is preferable to secure data and programs that demand a high level of security with Blowfish. Conclusions: From the experimental results, the modified Blowfish algorithm performs faster than normal Blowfish in terms of time complexity with an average execution time of 250.0 ms for normal Blowfish and 248.4 ms for the modified Blowfish algorithm. Therefore, it can be concluded that the modified Blowfish algorithm using the F-structure is time-efficient while normal Blowfish is better in terms of security.

Cloud computing has spread widely among different organizations due to its advantages, such as cost reduction, resource pooling, broad network access, and ease of administration. It increases the abilities of physical resources by optimizing shared use. Clients’ valuable items (data and applications) are moved outside of regulatory supervision in a shared environment where many clients are grouped together. However, this process poses security concerns, such as sensitive information theft and personally identifiable data leakage. Many researchers have contributed to reducing the problem of data security in cloud computing by developing a variety of technologies to secure cloud data, including encryption. In this study, a set of encryption algorithms (advance encryption standard (AES), data encryption standard (DES), Blowfish, Rivest-Shamir-Adleman (RSA) encryption, and international data encryption algorithm (IDEA) was compared in terms of security, data encipherment capacity, memory usage, and encipherment time to determine the optimal algorithm for securing cloud information from hackers. Results show that RSA and IDEA are less secure than AES, Blowfish, and DES). The AES algorithm encrypts a huge amount of data, takes the least encipherment time, and is faster than other algorithms, and the Blowfish algorithm requires the least amount of memory space.

During the last five years, spiking neural P (SN P) systems have attracted a lot of attention in the field of cryptography since these systems can more efficiently support advanced and complex cryptographic algorithms due to their high computational capabilities. Specifically, these systems can be seen as a potential solution to efficiently performing asymmetric algorithms, which are more demanding than symmetric systems. This factor becomes critical, especially in resource-constrained single-board computer systems, since many of these systems are currently used to ensure the security of IoT applications in portable systems. In this work, we present for the first time the implementation of an asymmetric encryption algorithm called ElGamal based on spiking neural P systems and their cutting-edge variants. The proposed design involves the encryption and decryption processes. Specifically, we propose the design of a neural network to efficiently perform the extended Euclidean algorithm used in the decryption task. Here, we exert major efforts to create a compact and high-performance circuit to perform the extended Euclidean algorithm since the calculation of this algorithm is the most demanding when the decryption process is required. Finally, we perform several tests to show the computational capabilities of our proposal in comparison to conventional implementations on single-board computer systems. Our results show that the proposed encryption/decryption scheme potentially allows its use to ensure confidentiality, data integrity, and secure authentication, among other applications for resource-constrained embedded systems.

The Internet of Things (IoT) is a system of interconnected materials that have software, detectors, and network integration embedded that make it possible to gather information and communicate. But as the number of connected devices grows rapidly, privacy and security concerns raised by the IoT have been the primary concerns. IoT devices are vulnerable to a range of security hazards, including malware attacks, unauthorised access, and data breaches, which may jeopardise the confidentiality, integrity, and accessibility of the data they collect and process. This paper aims to provide a brief overview of IoT security, which helps identify the most significant issues with IoT ecosystem security and safety. The survey focuses on the cryptographic techniques that are used to provide security to IoT devices and summarises the proposed Internet of Things safeguarding algorithms.

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.

With the explosion of connected devices linked to one another, the amount of transmitted data grows day by day, posing new problems in terms of information security, such as unauthorized access to users’ credentials and sensitive information. Therefore, this study employed RSA and ElGamal cryptographic algorithms with the application of SHA-256 for digital signature formulation to enhance security and validate the sharing of sensitive information. Security is increasingly becoming a complex task to achieve. The goal of this study is to be able to authenticate shared data with the application of the SHA-256 function to the cryptographic algorithms. The methodology employed involved the use of C# programming language for the implementation of the RSA and ElGamal cryptographic algorithms using the SHA-256 hash function for digital signature. The experimental result shows that the RSA algorithm performs better than the ElGamal during the encryption and signature verification processes, while ElGamal performs better than RSA during the decryption and signature generation process.