Oshan Mudannayake^1,#, Amila Indika^2,#, Upul Jayasinghe², Gyu Myoung Lee^3,*, Janaka Alawatugoda⁴

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2527-2578, 2025, DOI:10.32604/cmc.2025.068875 - 23 September 2025

Abstract The rapid adoption of machine learning in sensitive domains, such as healthcare, finance, and government services, has heightened the need for robust, privacy-preserving techniques. Traditional machine learning approaches lack built-in privacy mechanisms, exposing sensitive data to risks, which motivates the development of Privacy-Preserving Machine Learning (PPML) methods. Despite significant advances in PPML, a comprehensive and focused exploration of Secure Multi-Party Computing (SMPC) within this context remains underdeveloped. This review aims to bridge this knowledge gap by systematically analyzing the role of SMPC in PPML, offering a structured overview of current techniques, challenges, and future directions. More >

Asmat Ullah¹, Yar Muhammad^1,*, Bakht Zada¹, Korhan Cengiz², Nikola Ivković^3,*, Mario Konecki³, Abid Yahya⁴

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3767-3786, 2025, DOI:10.32604/cmc.2025.067145 - 23 September 2025

Abstract Low visibility conditions, particularly those caused by fog, significantly affect road safety and reduce drivers’ ability to see ahead clearly. The conventional approaches used to address this problem primarily rely on instrument-based and fixed-threshold-based theoretical frameworks, which face challenges in adaptability and demonstrate lower performance under varying environmental conditions. To overcome these challenges, we propose a real-time visibility estimation model that leverages roadside CCTV cameras to monitor and identify visibility levels under different weather conditions. The proposed method begins by identifying specific regions of interest (ROI) in the CCTV images and focuses on extracting specific… More >

Michael Juma Ayuma^1,*, Shem Mbandu Angolo¹, Philemon Nthenge Kasyoka², Simon Maina Karume³

Journal of Cyber Security, Vol.7, pp. 307-341, 2025, DOI:10.32604/jcs.2025.067360 - 02 September 2025

Abstract Token transmission is a fundamental component in diverse domains, including computer networks, blockchain systems, distributed architectures, financial transactions, secure communications, and identity verification. Ensuring optimal performance during transmission is essential for maintaining the efficiency of data in transit. However, persistent threats from adversarial actors continue to pose significant risks to the integrity, authenticity, and confidentiality of transmitted data. This study presents a comprehensive review of existing research on token transmission techniques, examining the roles of transmission channels, emerging trends, and the associated security and performance implications. A critical analysis is conducted to assess the strengths, More >

Ibtisam A. Taqi^*, Sarab M. Hameed

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1653-1674, 2025, DOI:10.32604/cmc.2025.067524 - 29 August 2025

Abstract The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated… More >

Kevin Santiago Rey Rodriguez, Julián David Avellaneda Galindo, Josep Tárrega Juan, Juan Ramón Bermejo Higuera^*, Javier Bermejo Higuera, Juan Antonio Sicilia Montalvo

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1807-1858, 2025, DOI:10.32604/cmc.2025.067127 - 29 August 2025

Abstract In today’s rapidly evolving digital landscape, web application security has become paramount as organizations face increasingly sophisticated cyber threats. This work presents a comprehensive methodology for implementing robust security measures in modern web applications and the proof of the Methodology applied to Vue.js, Spring Boot, and MySQL architecture. The proposed approach addresses critical security challenges through a multi-layered framework that encompasses essential security dimensions including multi-factor authentication, fine-grained authorization controls, sophisticated session management, data confidentiality and integrity protection, secure logging mechanisms, comprehensive error handling, high availability strategies, advanced input validation, and security headers implementation. Significant… More >

Ahmed I. Alutaibi^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 875-903, 2025, DOI:10.32604/cmc.2025.067078 - 29 August 2025

Abstract The rapid evolution of quantum computing poses significant threats to traditional cryptographic schemes, particularly in Decentralized Finance (DeFi) systems that rely on legacy mechanisms like RSA and ECDSA for digital identity verification. This paper proposes a quantum-resilient, blockchain-based identity verification framework designed to address critical challenges in privacy preservation, scalability, and post-quantum security. The proposed model integrates Post-quantum Cryptography (PQC), specifically lattice-based cryptographic primitives, with Decentralized Identifiers (DIDs) and Zero-knowledge Proofs (ZKPs) to ensure verifiability, anonymity, and resistance to quantum attacks. A dual-layer architecture is introduced, comprising an identity layer for credential generation and validation,… More >

Maazen Alsabaan¹, Jasmin Praful Bharadiya², Vishwanath Eswarakrishnan³, Adnan Mustafa Cheema⁴, Zaid Bin Faheem⁵, Jehad Ali^6,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1135-1160, 2025, DOI:10.32604/cmc.2025.066969 - 29 August 2025

Abstract The healthcare sector involves many steps to ensure efficient care for patients, such as appointment scheduling, consultation plans, online follow-up, and more. However, existing healthcare mechanisms are unable to facilitate a large number of patients, as these systems are centralized and hence vulnerable to various issues, including single points of failure, performance bottlenecks, and substantial monetary costs. Furthermore, these mechanisms are unable to provide an efficient mechanism for saving data against unauthorized access. To address these issues, this study proposes a blockchain-based authentication mechanism that authenticates all healthcare stakeholders based on their credentials. Furthermore, also… More >

Abdulatif Alabdulatif^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1185-1220, 2025, DOI:10.32604/cmc.2025.066898 - 29 August 2025

Abstract FedCognis is a secure and scalable federated learning framework designed for continuous anomaly detection in Industrial Internet of Things-enabled Cognitive Cities (IIoTCC). It introduces two key innovations: a Quantum Secure Authentication (QSA) mechanism for adversarial defense and integrity validation, and a Self-Attention Long Short-Term Memory (SALSTM) model for high-accuracy spatiotemporal anomaly detection. Addressing core challenges in traditional Federated Learning (FL)—such as model poisoning, communication overhead, and concept drift—FedCognis integrates dynamic trust-based aggregation and lightweight cryptographic verification to ensure secure, real-time operation across heterogeneous IIoT domains including utilities, public safety, and traffic systems. Evaluated on the More >

Mohammed Naif Alatawi^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 695-727, 2025, DOI:10.32604/cmc.2025.066606 - 29 August 2025

Abstract Adaptive robust secure framework plays a vital role in implementing intelligent automation and decentralized decision making of Industry 5.0. Latency, privacy risks and the complexity of industrial networks have been preventing attempts at traditional cloud-based learning systems. We demonstrate that, to overcome these challenges, for instance, the EdgeGuard-IoT framework, a 6G edge intelligence framework enhancing cybersecurity and operational resilience of the smart grid, is needed on the edge to integrate Secure Federated Learning (SFL) and Adaptive Anomaly Detection (AAD). With ultra-reliable low latency communication (URLLC) of 6G, artificial intelligence-based network orchestration, and massive machine type… More >

Tsu-Yang Wu^1,2, Haozhi Wu², Maoxin Tang³, Saru Kumari⁴, Chien-Ming Chen^1,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1715-1732, 2025, DOI:10.32604/cmc.2025.065560 - 29 August 2025

Abstract With the rapid development and widespread adoption of Internet of Things (IoT) technology, the innovative concept of the Internet of Vehicles (IoV) has emerged, ushering in a new era of intelligent transportation. Since vehicles are mobile entities, they move across different domains and need to communicate with the Roadside Unit (RSU) in various regions. However, open environments are highly susceptible to becoming targets for attackers, posing significant risks of malicious attacks. Therefore, it is crucial to design a secure authentication protocol to ensure the security of communication between vehicles and RSUs, particularly in scenarios where More >