Ammar Odeh^*, Anas Abu Taleb

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 447-461, 2025, DOI:10.32604/cmc.2025.065426 - 09 June 2025

Abstract The increasing deployment of Internet of Things (IoT) devices has introduced significant security challenges, including identity spoofing, unauthorized access, and data integrity breaches. Traditional security mechanisms rely on centralized frameworks that suffer from single points of failure, scalability issues, and inefficiencies in real-time security enforcement. To address these limitations, this study proposes the Blockchain-Enhanced Trust and Access Control for IoT Security (BETAC-IoT) model, which integrates blockchain technology, smart contracts, federated learning, and Merkle tree-based integrity verification to enhance IoT security. The proposed model eliminates reliance on centralized authentication by employing decentralized identity management, ensuring tamper-proof… More >

Mohammad Tabrez Quasim^1,*, Khair Ul Nisa¹, Mohammad Shahid Husain², Abakar Ibraheem Abdalla Aadam¹, Mohammed Waseequ Sheraz¹, Mohammad Zunnun Khan¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1169-1187, 2025, DOI:10.32604/cmc.2025.062989 - 09 June 2025

Abstract Smart edge computing (SEC) is a novel paradigm for computing that could transfer cloud-based applications to the edge network, supporting computation-intensive services like face detection and natural language processing. A core feature of mobile edge computing, SEC improves user experience and device performance by offloading local activities to edge processors. In this framework, blockchain technology is utilized to ensure secure and trustworthy communication between edge devices and servers, protecting against potential security threats. Additionally, Deep Learning algorithms are employed to analyze resource availability and optimize computation offloading decisions dynamically. IoT applications that require significant resources… More >

Peiying Zhang^1,2,*, Yihong Yu^1,2, Jing Liu³, Chong Lv^1,2, Lizhuang Tan^4,5, Yulin Zhang^6,7,8

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4393-4409, 2025, DOI:10.32604/cmc.2025.064654 - 19 May 2025

Abstract As Internet of Things (IoT) technologies continue to evolve at an unprecedented pace, intelligent big data control and information systems have become critical enablers for organizational digital transformation, facilitating data-driven decision making, fostering innovation ecosystems, and maintaining operational stability. In this study, we propose an advanced deployment algorithm for Service Function Chaining (SFC) that leverages an enhanced Practical Byzantine Fault Tolerance (PBFT) mechanism. The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings. By integrating blockchain technology and Deep Reinforcement Learning (DRL), our algorithm not… More >

Arshiya Sajid Ansari^1,*, Ghadir Altuwaijri², Fahad Alodhyani¹, Moulay Ibrahim El-Khalil Ghembaza³, Shahabas Manakunnath Devasam Paramb³, Mohammad Sajid Mohammadi³

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3713-3752, 2025, DOI:10.32604/cmc.2025.064027 - 19 May 2025

Abstract IoT has emerged as a game-changing technology that connects numerous gadgets to networks for communication, processing, and real-time monitoring across diverse applications. Due to their heterogeneous nature and constrained resources, as well as the growing trend of using smart gadgets, there are privacy and security issues that are not adequately managed by conventional security measures. This review offers a thorough analysis of contemporary AI solutions designed to enhance security within IoT ecosystems. The intersection of AI technologies, including ML, and blockchain, with IoT privacy and security is systematically examined, focusing on their efficacy in addressing… More >

Yogendra P. S. Maravi^*, Nishchol Mishra

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5517-5537, 2025, DOI:10.32604/cmc.2025.063964 - 19 May 2025

Abstract The growing demand for international travel has highlighted the critical need for reliable tools to verify travelers’ healthcare status and meet entry requirements. Personal health passports, while essential, face significant challenges related to data silos, privacy protection, and forgery risks in global sharing. To address these issues, this study proposes a blockchain-based solution designed for the secure storage, sharing, and verification of personal health passports. This innovative approach combines on-chain and off-chain storage, leveraging searchable encryption to enhance data security and optimize blockchain storage efficiency. By reducing the storage burden on the blockchain, the system… More >

Yuling Luo^1,2, Xiaoguang Lin^1,2, Junxiu Liu^1,2,*, Qiang Fu^1,2, Sheng Qin^1,2, Zhen Min^1,2, Tinghua Hu^1,2

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5323-5343, 2025, DOI:10.32604/cmc.2025.063860 - 19 May 2025

Abstract The majors accredited by the Engineering Education Accreditation (EEA) reflect the accreditation agency’s recognition of the school’s engineering programs. Excellent accreditation management holds significant importance for the advancement of engineering education programs. However, the traditional engineering education system framework suffers from the opacity of raw education data and the difficulty for accreditation bodies to forensically examine the self-assessment reports. To solve these issues, an EEA framework based on Hyperledger Fabric blockchain technology is proposed in this work. Firstly, all relevant stakeholders and information interactions occur within the blockchain network, ensuring the authenticity of educational data More >

Tianyu Li¹, Dezhi Han¹, Jiatao Li¹, Kuan-Ching Li^2,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4117-4140, 2025, DOI:10.32604/cmc.2025.063630 - 19 May 2025

Abstract As is known, centralized federated learning faces risks of a single point of failure and privacy breaches, and blockchain-based federated learning frameworks can address these challenges to a certain extent in recent works. However, malicious clients may still illegally access the blockchain to upload malicious data or steal on-chain data. In addition, blockchain-based federated training suffers from a heavy storage burden and excessive network communication overhead. To address these issues, we propose an asynchronous, tiered federated learning storage scheme based on blockchain and IPFS. It manages the execution of federated learning tasks through smart contracts… More >

Hongliang Tian, Zhong Fan^*, Zhiyang Ruan, Aomen Zhao

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5199-5217, 2025, DOI:10.32604/cmc.2025.063274 - 19 May 2025

Abstract With the continuous growth of exponential data in IoT, it is usually chosen to outsource data to the cloud server. However, cloud servers are usually provided by third parties, and there is a risk of privacy leakage. Encrypting data can ensure its security, but at the same time, it loses the retrieval function of IoT data. Searchable Encryption (SE) can achieve direct retrieval based on ciphertext data. The traditional searchable encryption scheme has the problems of imperfect function, low retrieval efficiency, inaccurate retrieval results, and centralized cloud servers being vulnerable and untrustworthy. This paper proposes… More >

Shrabani Sutradhar^1,2, Rajesh Bose³, Sudipta Majumder¹, Arfat Ahmad Khan^4,*, Sandip Roy³, Fasee Ullah⁵, Deepak Prashar^6,7

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3975-4029, 2025, DOI:10.32604/cmc.2025.061965 - 19 May 2025

Abstract Cloud-based setups are intertwined with the Internet of Things and advanced, and technologies such as blockchain revolutionize conventional healthcare infrastructure. This digitization has major advantages, mainly enhancing the security barriers of the green tree infrastructure. In this study, we conducted a systematic review of over 150 articles that focused exclusively on blockchain-based healthcare systems, security vulnerabilities, cyberattacks, and system limitations. In addition, we considered several solutions proposed by thousands of researchers worldwide. Our results mostly delineate sustained threats and security concerns in blockchain-based medical health infrastructures for data management, transmission, and processing. Here, we describe… More >

Jiling Wan, Lifeng Cao^*, Jinlong Bai, Jinhui Li, Xuehui Du

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4775-4794, 2025, DOI:10.32604/cmc.2025.061964 - 19 May 2025

Abstract Blockchain platforms with the unique characteristics of anonymity, decentralization, and transparency of their transactions, which are faced with abnormal activities such as money laundering, phishing scams, and fraudulent behavior, posing a serious threat to account asset security. For these potential security risks, this paper proposes a hybrid neural network detection method (HNND) that learns multiple types of account features and enhances fusion information among them to effectively detect abnormal transaction behaviors in the blockchain. In HNND, the Temporal Transaction Graph Attention Network (T2GAT) is first designed to learn biased aggregation representation of multi-attribute transactions among More >