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 >

Sulaiman Al Amro^*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4623-4658, 2025, DOI:10.32604/cmc.2025.063734 - 19 May 2025

Abstract The rapid proliferation of Internet of Things (IoT) devices has heightened security concerns, making intrusion detection a pivotal challenge in safeguarding these networks. Traditional centralized Intrusion Detection Systems (IDS) often fail to meet the privacy requirements and scalability demands of large-scale IoT ecosystems. To address these challenges, we propose an innovative privacy-preserving approach leveraging Federated Learning (FL) for distributed intrusion detection. Our model eliminates the need for aggregating sensitive data on a central server by training locally on IoT devices and sharing only encrypted model updates, ensuring enhanced privacy and scalability without compromising detection accuracy.… More >

Zhipeng Qin^1,2,*, Hanbing Yan³, Biyang Zhang², Peng Wang², Yitao Li³

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5811-5829, 2025, DOI:10.32604/cmc.2025.063308 - 19 May 2025

Abstract With the widespread adoption of encrypted Domain Name System (DNS) technologies such as DNS over Hyper Text Transfer Protocol Secure (HTTPS), traditional port and protocol-based traffic analysis methods have become ineffective. Although encrypted DNS enhances user privacy protection, it also provides concealed communication channels for malicious software, compelling detection technologies to shift towards statistical feature-based and machine learning approaches. However, these methods still face challenges in real-time performance and privacy protection. This paper proposes a real-time identification technology for encrypted DNS traffic with privacy protection. Firstly, a hierarchical architecture of cloud-edge-end collaboration is designed, incorporating More >

Junjie Cao^1,2, Zhiyong Yu^2,*, Xiaotao Xu¹, Baohong Zhu³, Jian Yang²

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5235-5257, 2025, DOI:10.32604/cmc.2025.062371 - 19 May 2025

Abstract This paper introduces a quantum-enhanced edge computing framework that synergizes quantum-inspired algorithms with advanced machine learning techniques to optimize real-time task offloading in edge computing environments. This innovative approach not only significantly improves the system’s real-time responsiveness and resource utilization efficiency but also addresses critical challenges in Internet of Things (IoT) ecosystems—such as high demand variability, resource allocation uncertainties, and data privacy concerns—through practical solutions. Initially, the framework employs an adaptive adjustment mechanism to dynamically manage task and resource states, complemented by online learning models for precise predictive analytics. Secondly, it accelerates the search for… 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 >

Rongsen Wu¹, Jie Xu¹, Yuhang Zhang¹, Changming Zhao^2,*, Yiweng Xie³, Zelei Wu¹, Yunji Li², Jinhong Guo⁴, Shiyang Tang^5,6

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4961-4978, 2025, DOI:10.32604/cmc.2025.061396 - 19 May 2025

Abstract With the rapid development of artificial intelligence and Internet of Things technologies, video action recognition technology is widely applied in various scenarios, such as personal life and industrial production. However, while enjoying the convenience brought by this technology, it is crucial to effectively protect the privacy of users’ video data. Therefore, this paper proposes a video action recognition method based on personalized federated learning and spatiotemporal features. Under the framework of federated learning, a video action recognition method leveraging spatiotemporal features is designed. For the local spatiotemporal features of the video, a new differential information… More >

Mozhgan Gholami¹, Ali Ghaffari^1,2,3,*, Nahideh Derakhshanfard¹, Nadir iBRAHIMOĞLU⁴, Ali Asghar Pourhaji Kazem²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1561-1605, 2025, DOI:10.32604/cmc.2025.063304 - 16 April 2025

Abstract The Internet has been enhanced recently by blockchain and Internet of Things (IoT) networks. The Internet of Things is a network of various sensor-equipped devices. It gradually integrates the Internet, sensors, and cloud computing. Blockchain is based on encryption algorithms, which are shared database technologies on the Internet. Blockchain technology has grown significantly because of its features, such as flexibility, support for integration, anonymity, decentralization, and independent control. Computational nodes in the blockchain network are used to verify online transactions. However, this integration creates scalability, interoperability, and security challenges. Over the last decade, several advancements… More >

Conghuan Ye^1,*, Shenglong Tan¹, Shi Li¹, Jun Wang¹, Qiankun Zuo¹, Bing Xiong²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2927-2946, 2025, DOI:10.32604/cmc.2025.062051 - 16 April 2025

Abstract With the fast development of multimedia social platforms, content dissemination on social media platforms is becoming more popular. Social image sharing can also raise privacy concerns. Image encryption can protect social images. However, most existing image protection methods cannot be applied to multimedia social platforms because of encryption in the spatial domain. In this work, the authors propose a secure social image-sharing method with watermarking/fingerprinting and encryption. First, the fingerprint code with a hierarchical community structure is designed based on social network analysis. Then, discrete wavelet transform (DWT) from block discrete cosine transform (DCT) directly… More >

Muhammad Saad, Ki-Woong Park^*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1881-1900, 2025, DOI:10.32604/cmc.2025.061733 - 16 April 2025

Abstract The proliferation of Internet of Things (IoT) devices introduces substantial security challenges. Currently, privacy constitutes a significant concern for individuals. While maintaining privacy within these systems is an essential characteristic, it often necessitates certain compromises, such as complexity and scalability, thereby complicating management efforts. The principal challenge lies in ensuring confidentiality while simultaneously preserving individuals’ anonymity within the system. To address this, we present our proposed architecture for managing IoT devices using blockchain technology. Our proposed architecture works on and off blockchain and is integrated with dashcams and closed-circuit television (CCTV) security cameras. In this… More >

Kaiyang Han¹, Xiaoqiang Jia¹, Yangfei Lin², Tsutomu Yoshinaga², Yalong Li², Jiale Wu^2,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2971-2988, 2025, DOI:10.32604/cmc.2025.061563 - 16 April 2025

Abstract With the rapid development of artificial intelligence and the Internet of Things, along with the growing demand for privacy-preserving transmission, the need for efficient and secure communication systems has become increasingly urgent. Traditional communication methods transmit data at the bit level without considering its semantic significance, leading to redundant transmission overhead and reduced efficiency. Semantic communication addresses this issue by extracting and transmitting only the most meaningful semantic information, thereby improving bandwidth efficiency. However, despite reducing the volume of data, it remains vulnerable to privacy risks, as semantic features may still expose sensitive information. To… More >