Yanan Liu^1,*, Suhao Wang^1,*, Lei Cao¹, Pengfei Wang¹, Zheng Zhang², Shuo Qiu¹, Ruchan Dong¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072710 - 12 January 2026

Abstract Unmanned Aerial Vehicles (UAVs) in Flying Ad-Hoc Networks (FANETs) are widely used in both civilian and military fields, but they face severe security, trust, and privacy vulnerabilities due to their high mobility, dynamic topology, and open wireless channels. Existing security protocols for Mobile Ad-Hoc Networks (MANETs) cannot be directly applied to FANETs, as FANETs require lightweight, high real-time performance, and strong anonymity. The current FANETs security protocol cannot simultaneously meet the requirements of strong anonymity, high security, and low overhead in high dynamic and resource-constrained scenarios. To address these challenges, this paper proposes an Anonymous Authentication… More >

Muntaham Inaam Hashmi¹, Muhammad Ayaz Khan², Khwaja Mansoor ul Hassan¹, Suliman A. Alsuhibany^3,*, Ainur Abduvalova⁴, Asfandyar Khan⁵

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071452 - 12 January 2026

Abstract Cyber-criminals target smart connected devices for spyware distribution and security breaches, but existing Internet of Things (IoT) security standards are insufficient. Major IoT industry players prioritize market share over security, leading to insecure smart products. Traditional host-based protection solutions are less effective due to limited resources. Overcoming these challenges and enhancing the security of IoT Devices requires a security design at the network level that uses lightweight cryptographic parameters. In order to handle control, administration, and security concerns in traditional networking, the Gateway Node offers a contemporary networking architecture. By managing all network-level computations and… More >

D. Bernal^*, O. Ledesma, P. Lamo, J. Bermejo

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-39, 2026, DOI:10.32604/cmc.2025.069746 - 10 November 2025

Abstract This work evaluates an architecture for decentralized authentication of Internet of Things (IoT) devices in Low Earth Orbit (LEO) satellite networks using IOTA Identity technology. To the best of our knowledge, it is the first proposal to integrate IOTA’s Directed Acyclic Graph (DAG)-based identity framework into satellite IoT environments, enabling lightweight and distributed authentication under intermittent connectivity. The system leverages Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs) over the Tangle, eliminating the need for mining and sequential blocks. An identity management workflow is implemented that supports the creation, validation, deactivation, and reactivation of IoT devices,… More >

Hui Wei^1,2, Zhanfei Ma^1,3,*, Jing Jiang¹, Bisheng Wang¹, Zhong Di¹

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-25, 2026, DOI:10.32604/cmc.2025.069236 - 10 November 2025

Abstract The Internet of Vehicles (IoV) operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms. Existing methods often suffer from complex certificate management, inefficient consensus protocols, and poor resilience in high-frequency communication, resulting in high latency, poor scalability, and unstable network performance. To address these issues, this paper proposes a secure and efficient distributed authentication scheme for IoV with reputation-driven consensus and SM9. First, this paper proposes a decentralized authentication architecture that utilizes the certificate-free feature of SM9, enabling lightweight authentication and key negotiation, thereby… More >

Edward Danso Ansong^*, Simon Bonsu Osei^*, Raphael Adjetey Adjei

Journal of Cyber Security, Vol.7, pp. 533-564, 2025, DOI:10.32604/jcs.2025.061821 - 11 December 2025

Abstract The surge in identity fraud, driven by the rapid adoption of mobile money, internet banking, and e-services during the COVID-19 pandemic, underscores the need for robust cybersecurity solutions. Zero-Knowledge Proofs (ZKPs) enable secure identity verification by allowing individuals to prove possession of a National ID card without revealing sensitive information. This study implements a ZKP-based identity verification system using Camenisch-Lysyanskaya (CL) signatures, reducing reliance on complex trusted setup ceremonies. While a trusted issuer is still required, as assumed in this work, our approach eliminates the need for broader system-wide trusted parameters. We evaluate the system’s More >

Marwa Ahmim¹, Nour Ouafi¹, Insaf Ullah^2,*, Ahmed Ahmim³, Djalel Chefrour³, Reham Almukhlifi⁴

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5093-5116, 2025, DOI:10.32604/cmc.2025.067641 - 23 October 2025

Abstract The Internet of Healthcare Things (IoHT) marks a significant breakthrough in modern medicine by enabling a new era of healthcare services. IoHT supports real-time, continuous, and personalized monitoring of patients’ health conditions. However, the security of sensitive data exchanged within IoHT remains a major concern, as the widespread connectivity and wireless nature of these systems expose them to various vulnerabilities. Potential threats include unauthorized access, device compromise, data breaches, and data alteration, all of which may compromise the confidentiality and integrity of patient information. In this paper, we provide an in-depth security analysis of LAP-IoHT,… More >

Victor Otieno Mony^*, Anselemo Peters Ikoha, Roselida O. Maroko

Journal of Cyber Security, Vol.7, pp. 395-415, 2025, DOI:10.32604/jcs.2025.070952 - 30 September 2025

Abstract The widespread adoption of Cloud-Based Services has significantly increased the surface area for cyber threats, particularly targeting authentication mechanisms, which remain among the most vulnerable components of cloud security. This study aimed to address these challenges by developing and evaluating an Intelligent Zero Trust Architecture model tailored to mitigate authentication-related threats in Cloud-Based Services environments. Data was sourced from public repositories, including Kaggle and the National Institute for Standards and Technology MITRE Corporation’s Adversarial Tactics, Techniques, & Common Knowledge (ATT&CK) framework. The study utilized two trust signals: Behavioral targeting system users and Contextual targeting system… More >

Raj Sonani¹, Reham Alhejaili^2,*, Pushpalika Chatterjee³, Khalid Hamad Alnafisah⁴, Jehad Ali^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3169-3189, 2025, DOI:10.32604/cmes.2025.070225 - 30 September 2025

Abstract Healthcare networks are transitioning from manual records to electronic health records, but this shift introduces vulnerabilities such as secure communication issues, privacy concerns, and the presence of malicious nodes. Existing machine and deep learning-based anomalies detection methods often rely on centralized training, leading to reduced accuracy and potential privacy breaches. Therefore, this study proposes a Blockchain-based-Federated Learning architecture for Malicious Node Detection (BFL-MND) model. It trains models locally within healthcare clusters, sharing only model updates instead of patient data, preserving privacy and improving accuracy. Cloud and edge computing enhance the model’s scalability, while blockchain ensures More >

Ramadan Abdul-Rashid¹, Mohd Amiruddin Abd Rahman^1,*, Abdulaziz Yagoub Barnawi²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3213-3250, 2025, DOI:10.32604/cmes.2025.066589 - 30 September 2025

Abstract Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks (WSNs), especially in security-critical, time-sensitive applications. However, most existing protocols degrade substantially under malicious interference. We introduce iSTSP, an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust, precise synchronization even in hostile environments: (1) trust preprocessing that filters node participation using behavioral trust scoring; (2) anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time; (3) reliability-weighted consensus that prioritizes high-trust nodes during time aggregation; and (4) convergence-optimized synchronization… More >

Siham Essahraui¹, Ismail Lamaakal¹, Yassine Maleh^2,*, Khalid El Makkaoui¹, Mouncef Filali Bouami¹, Ibrahim Ouahbi¹, May Almousa³, Ali Abdullah S. AlQahtani⁴, Ahmed A. Abd El-Latif^5,6

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3151-3183, 2025, DOI:10.32604/cmc.2025.067359 - 23 September 2025

Abstract The rapid shift to online education has introduced significant challenges to maintaining academic integrity in remote assessments, as traditional proctoring methods fall short in preventing cheating. The increase in cheating during online exams highlights the need for efficient, adaptable detection models to uphold academic credibility. This paper presents a comprehensive analysis of various deep learning models for cheating detection in online proctoring systems, evaluating their accuracy, efficiency, and adaptability. We benchmark several advanced architectures, including EfficientNet, MobileNetV2, ResNet variants and more, using two specialized datasets (OEP and OP) tailored for online proctoring contexts. Our findings More >