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 >

Saad Alahmari^1,*, Abdulwhab Alkharashi²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 849-873, 2025, DOI:10.32604/cmes.2025.062549 - 11 April 2025

Abstract The Internet of Things (IoT) is emerging as an innovative phenomenon concerned with the development of numerous vital applications. With the development of IoT devices, huge amounts of information, including users’ private data, are generated. IoT systems face major security and data privacy challenges owing to their integral features such as scalability, resource constraints, and heterogeneity. These challenges are intensified by the fact that IoT technology frequently gathers and conveys complex data, creating an attractive opportunity for cyberattacks. To address these challenges, artificial intelligence (AI) techniques, such as machine learning (ML) and deep learning (DL),… More >

Sang-Hoon Choi¹, Ki-Woong Park^2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4021-4039, 2025, DOI:10.32604/cmc.2025.061267 - 06 March 2025

Abstract The proliferation of Internet of Things (IoT) devices has established edge computing as a critical paradigm for real-time data analysis and low-latency processing. Nevertheless, the distributed nature of edge computing presents substantial security challenges, rendering it a prominent target for sophisticated malware attacks. Existing signature-based and behavior-based detection methods are ineffective against the swiftly evolving nature of malware threats and are constrained by the availability of resources. This paper suggests the Genetic Encoding for Novel Optimization of Malware Evaluation (GENOME) framework, a novel solution that is intended to improve the performance of malware detection and… More >

Haider H. Al-Mahmood^1,*, Saad N. Alsaad²

Intelligent Automation & Soft Computing, Vol.40, pp. 53-74, 2025, DOI:10.32604/iasc.2024.059691 - 10 January 2025

Abstract In secure communications, lightweight encryption has become crucial, particularly for resource-constrained applications such as embedded devices, wireless sensor networks, and the Internet of Things (IoT). As these systems proliferate, cryptographic approaches that provide robust security while minimizing computing overhead, energy consumption, and memory usage are becoming increasingly essential. This study examines lightweight encryption techniques utilizing chaotic maps to ensure secure data transmission. Two algorithms are proposed, both employing the Logistic map; the first approach utilizes two logistic chaotic maps, while the second algorithm employs a single logistic chaotic map. Algorithm 1, including a two-stage mechanism… More >

Hafida Assmi¹, Azidine Guezzaz¹, Said Benkirane¹, Mourade Azrour^2,*, Said Jabbour³, Nisreen Innab⁴, Abdulatif Alabdulatif⁵

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 443-466, 2025, DOI:10.32604/cmc.2024.059047 - 03 January 2025

Abstract Internet of Things (IoT) refers to the infrastructures that connect smart devices to the Internet, operating autonomously. This connectivity makes it possible to harvest vast quantities of data, creating new opportunities for the emergence of unprecedented knowledge. To ensure IoT securit, various approaches have been implemented, such as authentication, encoding, as well as devices to guarantee data integrity and availability. Among these approaches, Intrusion Detection Systems (IDS) is an actual security solution, whose performance can be enhanced by integrating various algorithms, including Machine Learning (ML) and Deep Learning (DL), enabling proactive and accurate detection of… More >

Ali Hassan¹, N. Nizam-Uddin², Asim Quddus³, Syed Rizwan Hassan⁴, Ateeq Ur Rehman^5,*, Salil Bharany⁶

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3499-3559, 2024, DOI:10.32604/cmc.2024.057877 - 19 December 2024

Abstract Enhancing the interconnection of devices and systems, the Internet of Things (IoT) is a paradigm-shifting technology. IoT security concerns are still a substantial concern despite its extraordinary advantages. This paper offers an extensive review of IoT security, emphasizing the technology’s architecture, important security elements, and common attacks. It highlights how important artificial intelligence (AI) is to bolstering IoT security, especially when it comes to addressing risks at different IoT architecture layers. We systematically examined current mitigation strategies and their effectiveness, highlighting contemporary challenges with practical solutions and case studies from a range of industries, such More >

Hosam Alhakami^*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 329-356, 2024, DOI:10.32604/cmc.2023.043439 - 30 January 2024

Abstract The rapid growth of the Internet of Things (IoT) operations has necessitated the incorporation of quantum computing technologies to meet its expanding needs. This integration is motivated by the need to solve the specific issues provided by the expansion of IoT and the potential benefits that quantum computing can offer in this scenario. The combination of IoT and quantum computing creates new privacy and security problems. This study examines the critical need to prevent potential security concerns from quantum computing in IoT applications. We investigate the incorporation of quantum computing approaches within IoT security frameworks,… More >

Jin Su Kim, Sungbum Pan^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1663-1678, 2023, DOI:10.32604/cmc.2023.043998 - 29 November 2023

Abstract As Internet of Things (IoT) technology develops, integrating network functions into diverse equipment introduces new challenges, particularly in dealing with counterfeit issues. Over the past few decades, research efforts have focused on leveraging electromyogram (EMG) for personal recognition, aiming to address security concerns. However, obtaining consistent EMG signals from the same individual is inherently challenging, resulting in data irregularity issues and consequently decreasing the accuracy of personal recognition. Notably, conventional studies in EMG-based personal recognition have overlooked the issue of data irregularities. This paper proposes an innovative approach to personal recognition that combines a siamese… More >

Yu-Rim Lee¹, Na-Eun Park¹, Seo-Yi Kim², Il-Gu Lee^1,2,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3465-3482, 2023, DOI:10.32604/cmc.2023.041196 - 08 October 2023

Abstract With the introduction of 5G technology, the application of Internet of Things (IoT) devices is expanding to various industrial fields. However, introducing a robust, lightweight, low-cost, and low-power security solution to the IoT environment is challenging. Therefore, this study proposes two methods using a data compression technique to detect malicious traffic efficiently and accurately for a secure IoT environment. The first method, compressed sensing and learning (CSL), compresses an event log in a bitmap format to quickly detect attacks. Then, the attack log is detected using a machine-learning classification model. The second method, precise re-learning… More >

Ali Ahmadi Shahrakht¹, Parisa Hajirahimi², Omid Rostami³, Diego Martín^4,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3059-3081, 2023, DOI:10.32604/iasc.2023.040502 - 11 September 2023

Abstract As the internet of things (IoT) continues to expand rapidly, the significance of its security concerns has grown in recent years. To address these concerns, physical unclonable functions (PUFs) have emerged as valuable tools for enhancing IoT security. PUFs leverage the inherent randomness found in the embedded hardware of IoT devices. However, it has been shown that some PUFs can be modeled by attackers using machine-learning-based approaches. In this paper, a new deep learning (DL)-based modeling attack is introduced to break the resistance of complex XAPUFs. Because training DL models is a problem that falls… More >