Menwa Alshammeri¹, Mamoona Humayun^2,*, Khalid Haseeb³, Ghadah Naif Alwakid¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 433-446, 2025, DOI:10.32604/cmc.2025.065660 - 09 June 2025

Abstract Wireless technologies and the Internet of Things (IoT) are being extensively utilized for advanced development in traditional communication systems. This evolution lowers the cost of the extensive use of sensors, changing the way devices interact and communicate in dynamic and uncertain situations. Such a constantly evolving environment presents enormous challenges to preserving a secure and lightweight IoT system. Therefore, it leads to the design of effective and trusted routing to support sustainable smart cities. This research study proposed a Genetic Algorithm sentiment-enhanced secured optimization model, which combines big data analytics and analysis rules to evaluate… More >

Ali Hamid Farea^1,*, Iman Askerzade^1,2, Omar H. Alhazmi³, Savaş Takan⁴

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1457-1484, 2025, DOI:10.32604/cmc.2025.064872 - 09 June 2025

Abstract Feature selection (FS) is a pivotal pre-processing step in developing data-driven models, influencing reliability, performance and optimization. Although existing FS techniques can yield high-performance metrics for certain models, they do not invariably guarantee the extraction of the most critical or impactful features. Prior literature underscores the significance of equitable FS practices and has proposed diverse methodologies for the identification of appropriate features. However, the challenge of discerning the most relevant and influential features persists, particularly in the context of the exponential growth and heterogeneity of big data—a challenge that is increasingly salient in modern artificial… More >

Hanqing Sun¹, Xue Li^2,*, Qiyuan Fan³, Puming Wang³

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1659-1679, 2025, DOI:10.32604/cmc.2025.061426 - 09 June 2025

Abstract The era of big data brings new challenges for information network systems (INS), simultaneously offering unprecedented opportunities for advancing intelligent intrusion detection systems. In this work, we propose a data-driven intrusion detection system for Distributed Denial of Service (DDoS) attack detection. The system focuses on intrusion detection from a big data perceptive. As intelligent information processing methods, big data and artificial intelligence have been widely used in information systems. The INS system is an important information system in cyberspace. In advanced INS systems, the network architectures have become more complex. And the smart devices in… 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 >

Sondes Baccouri^1,2,#,*, Takoua Abdellatif ^3,#

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1071-1093, 2025, DOI:10.32604/cmes.2025.062902 - 11 April 2025

Abstract Managing sensitive data in dynamic and high-stakes environments, such as healthcare, requires access control frameworks that offer real-time adaptability, scalability, and regulatory compliance. BIG-ABAC introduces a transformative approach to Attribute-Based Access Control (ABAC) by integrating real-time policy evaluation and contextual adaptation. Unlike traditional ABAC systems that rely on static policies, BIG-ABAC dynamically updates policies in response to evolving rules and real-time contextual attributes, ensuring precise and efficient access control. Leveraging decision trees evaluated in real-time, BIG-ABAC overcomes the limitations of conventional access control models, enabling seamless adaptation to complex, high-demand scenarios. The framework adheres to the… More >

Yongfeng Fang^1,3, Kong Fah Tee^2,*

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 771-771, 2025, DOI:10.32604/sdhm.2024.061036 - 03 April 2025

Abstract This article has no abstract. More >

Jipu Li¹, Haidong Shao^2,*, Yun Kong³, Zhuyun Chen⁴

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3609-3613, 2025, DOI:10.32604/cmc.2024.062183 - 17 February 2025

Abstract This article has no abstract. More >

Ali Alqarni^*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 389-406, 2025, DOI:10.32604/cmc.2024.059238 - 03 January 2025

Abstract Open networks and heterogeneous services in the Internet of Vehicles (IoV) can lead to security and privacy challenges. One key requirement for such systems is the preservation of user privacy, ensuring a seamless experience in driving, navigation, and communication. These privacy needs are influenced by various factors, such as data collected at different intervals, trip durations, and user interactions. To address this, the paper proposes a Support Vector Machine (SVM) model designed to process large amounts of aggregated data and recommend privacy-preserving measures. The model analyzes data based on user demands and interactions with service More >

Yuewei Wu¹, Ruiling Fu¹, Tongtong Xing¹, Fulian Yin^1,2,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 751-775, 2025, DOI:10.32604/cmc.2024.057606 - 03 January 2025

Abstract In the Internet era, recommendation systems play a crucial role in helping users find relevant information from large datasets. Class imbalance is known to severely affect data quality, and therefore reduce the performance of recommendation systems. Due to the imbalance, machine learning algorithms tend to classify inputs into the positive (majority) class every time to achieve high prediction accuracy. Imbalance can be categorized such as by features and classes, but most studies consider only class imbalance. In this paper, we propose a recommendation system that can integrate multiple networks to adapt to a large number… More >

Surbhi Bhatia Khan^1,2,*, Mohammad Alojail³, Mahesh Thyluru Ramakrishna⁴, Hemant Sharma⁵

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4895-4914, 2024, DOI:10.32604/cmc.2024.057585 - 19 December 2024

Abstract In Intelligent Manufacturing, Big Data and industrial information enable enterprises to closely monitor and respond to precise changes in both internal processes and external environmental factors, ensuring more informed decision-making and adaptive system management. It also promotes decision making and provides scientific analysis to enhance the efficiency of the operation, cost reduction, maximizing the process of production and so on. Various methods are employed to enhance productivity, yet achieving sustainable manufacturing remains a complex challenge that requires careful consideration. This study aims to develop a methodology for effective manufacturing sustainability by proposing a novel Hybrid… More >