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  • Open Access

    ARTICLE

    Privacy Preserving Federated Anomaly Detection in IoT Edge Computing Using Bayesian Game Reinforcement Learning

    Fatima Asiri1, Wajdan Al Malwi1, Fahad Masood2, Mohammed S. Alshehri3, Tamara Zhukabayeva4, Syed Aziz Shah5, Jawad Ahmad6,*

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3943-3960, 2025, DOI:10.32604/cmc.2025.066498 - 03 July 2025

    Abstract Edge computing (EC) combined with the Internet of Things (IoT) provides a scalable and efficient solution for smart homes. The rapid proliferation of IoT devices poses real-time data processing and security challenges. EC has become a transformative paradigm for addressing these challenges, particularly in intrusion detection and anomaly mitigation. The widespread connectivity of IoT edge networks has exposed them to various security threats, necessitating robust strategies to detect malicious activities. This research presents a privacy-preserving federated anomaly detection framework combined with Bayesian game theory (BGT) and double deep Q-learning (DDQL). The proposed framework integrates BGT… More >

  • Open Access

    ARTICLE

    A Multi-Objective Joint Task Offloading Scheme for Vehicular Edge Computing

    Yiwei Zhang, Xin Cui*, Qinghui Zhao

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2355-2373, 2025, DOI:10.32604/cmc.2025.065430 - 03 July 2025

    Abstract The rapid advance of Connected-Automated Vehicles (CAVs) has led to the emergence of diverse delay-sensitive and energy-constrained vehicular applications. Given the high dynamics of vehicular networks, unmanned aerial vehicles-assisted mobile edge computing (UAV-MEC) has gained attention in providing computing resources to vehicles and optimizing system costs. We model the computing offloading problem as a multi-objective optimization challenge aimed at minimizing both task processing delay and energy consumption. We propose a three-stage hybrid offloading scheme called Dynamic Vehicle Clustering Game-based Multi-objective Whale Optimization Algorithm (DVCG-MWOA) to address this problem. A novel dynamic clustering algorithm is designed… More >

  • Open Access

    ARTICLE

    Multi-Agent Reinforcement Learning for Moving Target Defense Temporal Decision-Making Approach Based on Stackelberg-FlipIt Games

    Rongbo Sun, Jinlong Fei*, Yuefei Zhu, Zhongyu Guo

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3765-3786, 2025, DOI:10.32604/cmc.2025.064849 - 03 July 2025

    Abstract Moving Target Defense (MTD) necessitates scientifically effective decision-making methodologies for defensive technology implementation. While most MTD decision studies focus on accurately identifying optimal strategies, the issue of optimal defense timing remains underexplored. Current default approaches—periodic or overly frequent MTD triggers—lead to suboptimal trade-offs among system security, performance, and cost. The timing of MTD strategy activation critically impacts both defensive efficacy and operational overhead, yet existing frameworks inadequately address this temporal dimension. To bridge this gap, this paper proposes a Stackelberg-FlipIt game model that formalizes asymmetric cyber conflicts as alternating control over attack surfaces, thereby capturing More >

  • Open Access

    ARTICLE

    Intelligent Vehicle Lane-Changing Strategy through Polynomial and Game Theory

    Buwei Dang, Huanming Chen*, Heng Zhang, Jixian Wang, Jian Zhou

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2003-2023, 2025, DOI:10.32604/cmc.2025.062653 - 16 April 2025

    Abstract This paper introduces a lane-changing strategy aimed at trajectory planning and tracking control for intelligent vehicles navigating complex driving environments. A fifth-degree polynomial is employed to generate a set of potential lane-changing trajectories in the Frenet coordinate system. These trajectories are evaluated using non-cooperative game theory, considering the interaction between the target vehicle and its surroundings. Models considering safety payoffs, speed payoffs, comfort payoffs, and aggressiveness are formulated to obtain a Nash equilibrium solution. This way, collision avoidance is ensured, and an optimal lane change trajectory is planned. Three game scenarios are discussed, and the More >

  • Open Access

    ARTICLE

    DRG-DCC: A Driving Risk Gaming Based Distributed Congestion Control Method for C-V2X Technology

    Lingqiu Zeng1, Peibing Sa1, Qingwen Han2, Lei Ye2,*, Letian Yang1, Cheng Zhang1, Jiqiang Cheng2

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2059-2086, 2025, DOI:10.32604/cmc.2025.060392 - 16 April 2025

    Abstract Congestion control is an inherent challenge of V2X (Vehicle to Everything) technologies. Due to the use of a broadcasting mechanism, channel congestion becomes severe with the increase in vehicle density. The researchers suggested reducing the frequency of packet dissemination to relieve congestion, which caused a rise in road driving risk. Obviously, high-risk vehicles should be able to send messages timely to alarm surrounding vehicles. Therefore, packet dissemination frequency should be set according to the corresponding vehicle’s risk level, which is hard to evaluate. In this paper, a two-stage fuzzy inference model is constructed to evaluate More >

  • Open Access

    ARTICLE

    Evolution Analysis of Network Attack and Defense Situation Based on Game Theory

    Haiyan Sun1,*, Chenglong Shao1, Jianwei Zhang1, Kun Wang2, Wanwei Huang1

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1451-1470, 2025, DOI:10.32604/cmc.2025.059724 - 26 March 2025

    Abstract To address the problem that existing studies lack analysis of the relationship between attack-defense game behaviors and situation evolution from the game perspective after constructing an attack-defense model, this paper proposes a network attack-defense game model (ADGM). Firstly, based on the assumption of incomplete information between the two sides of the game, the ADGM model is established, and methods of payoff quantification, equilibrium solution, and determination of strategy confrontation results are presented. Then, drawing on infectious disease dynamics, the network attack-defense situation is defined based on the density of nodes in various security states, and… More >

  • Open Access

    ARTICLE

    Computation Offloading in Edge Computing for Internet of Vehicles via Game Theory

    Jianhua Liu*, Jincheng Wei, Rongxin Luo, Guilin Yuan, Jiajia Liu, Xiaoguang Tu

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1337-1361, 2024, DOI:10.32604/cmc.2024.056286 - 15 October 2024

    Abstract With the rapid advancement of Internet of Vehicles (IoV) technology, the demands for real-time navigation, advanced driver-assistance systems (ADAS), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, and multimedia entertainment systems have made in-vehicle applications increasingly computing-intensive and delay-sensitive. These applications require significant computing resources, which can overwhelm the limited computing capabilities of vehicle terminals despite advancements in computing hardware due to the complexity of tasks, energy consumption, and cost constraints. To address this issue in IoV-based edge computing, particularly in scenarios where available computing resources in vehicles are scarce, a multi-master and multi-slave double-layer game model More >

  • Open Access

    ARTICLE

    A Data Intrusion Tolerance Model Based on an Improved Evolutionary Game Theory for the Energy Internet

    Song Deng1,*, Yiming Yuan2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3679-3697, 2024, DOI:10.32604/cmc.2024.052008 - 20 June 2024

    Abstract Malicious attacks against data are unavoidable in the interconnected, open and shared Energy Internet (EI), Intrusion tolerant techniques are critical to the data security of EI. Existing intrusion tolerant techniques suffered from problems such as low adaptability, policy lag, and difficulty in determining the degree of tolerance. To address these issues, we propose a novel adaptive intrusion tolerance model based on game theory that enjoys two-fold ideas: 1) it constructs an improved replica of the intrusion tolerance model of the dynamic equation evolution game to induce incentive weights; and 2) it combines a tournament competition More >

  • Open Access

    ARTICLE

    IoT Task Offloading in Edge Computing Using Non-Cooperative Game Theory for Healthcare Systems

    Dinesh Mavaluru1,*, Chettupally Anil Carie2, Ahmed I. Alutaibi3, Satish Anamalamudi2, Bayapa Reddy Narapureddy4, Murali Krishna Enduri2, Md Ezaz Ahmed1

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1487-1503, 2024, DOI:10.32604/cmes.2023.045277 - 29 January 2024

    Abstract In this paper, we present a comprehensive system model for Industrial Internet of Things (IIoT) networks empowered by Non-Orthogonal Multiple Access (NOMA) and Mobile Edge Computing (MEC) technologies. The network comprises essential components such as base stations, edge servers, and numerous IIoT devices characterized by limited energy and computing capacities. The central challenge addressed is the optimization of resource allocation and task distribution while adhering to stringent queueing delay constraints and minimizing overall energy consumption. The system operates in discrete time slots and employs a quasi-static approach, with a specific focus on the complexities of… More >

  • Open Access

    ARTICLE

    MF2-DMTD: A Formalism and Game-Based Reasoning Framework for Optimized Drone-Type Moving Target Defense

    Sang Seo1, Jaeyeon Lee2, Byeongjin Kim2, Woojin Lee2, Dohoon Kim3,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2595-2628, 2023, DOI:10.32604/cmc.2023.042668 - 29 November 2023

    Abstract Moving-target-defense (MTD) fundamentally avoids an illegal initial compromise by asymmetrically increasing the uncertainty as the attack surface of the observable defender changes depending on spatial-temporal mutations. However, the existing naive MTD studies were conducted focusing only on wired network mutations. And these cases have also been no formal research on wireless aircraft domains with attributes that are extremely unfavorable to embedded system operations, such as hostility, mobility, and dependency. Therefore, to solve these conceptual limitations, this study proposes normalized drone-type MTD that maximizes defender superiority by mutating the unique fingerprints of wireless drones and that… More >

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