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  • Open Access

    ARTICLE

    Lightweight Intrusion Detection Using Reservoir Computing

    Jiarui Deng1,2, Wuqiang Shen1,3, Yihua Feng4, Guosheng Lu5, Guiquan Shen1,3, Lei Cui1,3, Shanxiang Lyu1,2,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1345-1361, 2024, DOI:10.32604/cmc.2023.047079

    Abstract The blockchain-empowered Internet of Vehicles (IoV) enables various services and achieves data security and privacy, significantly advancing modern vehicle systems. However, the increased frequency of data transmission and complex network connections among nodes also make them more susceptible to adversarial attacks. As a result, an efficient intrusion detection system (IDS) becomes crucial for securing the IoV environment. Existing IDSs based on convolutional neural networks (CNN) often suffer from high training time and storage requirements. In this paper, we propose a lightweight IDS solution to protect IoV against both intra-vehicle and external threats. Our approach achieves superior performance, as demonstrated by… More >

  • Open Access

    REVIEW

    Wireless Positioning: Technologies, Applications, Challenges, and Future Development Trends

    Xingwang Li1,2, Hua Pang1, Geng Li1,*, Junjie Jiang1, Hui Zhang3, Changfei Gu4, Dong Yuan4

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1135-1166, 2024, DOI:10.32604/cmes.2023.031534

    Abstract The development of the fifth-generation (5G) mobile communication systems has entered the commercialization stage. 5G has a high data rate, low latency, and high reliability that can meet the basic demands of most industries and daily life, such as the Internet of Things (IoT), intelligent transportation systems, positioning, and navigation. The continuous progress and development of society have aroused wide concern. Positioning accuracy is the core demand for the applications, especially in complex environments such as airports, warehouses, supermarkets, and basements. However, many factors also affect the accuracy of positioning in those environments, for example, multipath effects, non-line-of-sight, and clock… More >

  • Open Access

    ARTICLE

    Secure and Reliable Routing in the Internet of Vehicles Network: AODV-RL with BHA Attack Defense

    Nadeem Ahmed1,*, Khalid Mohammadani2, Ali Kashif Bashir3,4,5, Marwan Omar6, Angel Jones7, Fayaz Hassan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 633-659, 2024, DOI:10.32604/cmes.2023.031342

    Abstract Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles (IoV). However, intricate security challenges are intertwined with technological progress: Vehicular ad hoc Networks (VANETs), a core component of IoV, face security issues, particularly the Black Hole Attack (BHA). This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability; also, BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes altogether. Recognizing the importance of this challenge, we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor (AODV-RL). The significance of… More >

  • Open Access

    ARTICLE

    Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

    Othman S. Al-Heety1,*, Zahriladha Zakaria1,*, Ahmed Abu-Khadrah2, Mahamod Ismail3, Sarmad Nozad Mahmood4, Mohammed Mudhafar Shakir5, Sameer Alani6, Hussein Alsariera1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2103-2127, 2024, DOI:10.32604/cmes.2023.029509

    Abstract Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision. In this article, these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data. The framework integrates Kalman filtering and Q-learning. Unlike smoothing Kalman filtering, our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error. Unlike traditional Q-learning, our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road… More >

  • Open Access

    ARTICLE

    Flexible Global Aggregation and Dynamic Client Selection for Federated Learning in Internet of Vehicles

    Tariq Qayyum1, Zouheir Trabelsi1,*, Asadullah Tariq1, Muhammad Ali2, Kadhim Hayawi3, Irfan Ud Din4

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1739-1757, 2023, DOI:10.32604/cmc.2023.043684

    Abstract Federated Learning (FL) enables collaborative and privacy-preserving training of machine learning models within the Internet of Vehicles (IoV) realm. While FL effectively tackles privacy concerns, it also imposes significant resource requirements. In traditional FL, trained models are transmitted to a central server for global aggregation, typically in the cloud. This approach often leads to network congestion and bandwidth limitations when numerous devices communicate with the same server. The need for Flexible Global Aggregation and Dynamic Client Selection in FL for the IoV arises from the inherent characteristics of IoV environments. These include diverse and distributed data sources, varying data quality,… More >

  • Open Access

    ARTICLE

    A Trusted Edge Resource Allocation Framework for Internet of Vehicles

    Yuxuan Zhong1, Siya Xu1, Boxian Liao1, Jizhao Lu2, Huiping Meng2, Zhili Wang1, Xingyu Chen1,*, Qinghan Li3

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2629-2644, 2023, DOI:10.32604/cmc.2023.035526

    Abstract With the continuous progress of information technique, assisted driving technology has become an effective technique to avoid traffic accidents. Due to the complex road conditions and the threat of vehicle information being attacked and tampered with, it is difficult to ensure information security. This paper uses blockchain to ensure the safety of driving information and introduces mobile edge computing technology to monitor vehicle information and road condition information in real time, calculate the appropriate speed, and plan a reasonable driving route for the driver. To solve these problems, this paper proposes a trusted edge resource allocation framework for assisted driving… More >

  • Open Access

    ARTICLE

    3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

    Dun Cao1, Jia Ru1, Jian Qin1, Amr Tolba2, Jin Wang1, Min Zhu3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1365-1384, 2024, DOI:10.32604/cmes.2023.030260

    Abstract Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles, people, transportation infrastructure, and networks, thereby realizing a more intelligent and efficient transportation system. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topological structure of IoV to have the high space and time complexity. Network modeling and structure recognition for 3D roads can benefit the description of topological changes for IoV. This paper proposes a 3D general road model based on discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on… More >

  • Open Access

    ARTICLE

    Single Image Desnow Based on Vision Transformer and Conditional Generative Adversarial Network for Internet of Vehicles

    Bingcai Wei, Di Wang, Zhuang Wang, Liye Zhang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1975-1988, 2023, DOI:10.32604/cmes.2023.027727

    Abstract With the increasing popularity of artificial intelligence applications, machine learning is also playing an increasingly important role in the Internet of Things (IoT) and the Internet of Vehicles (IoV). As an essential part of the IoV, smart transportation relies heavily on information obtained from images. However, inclement weather, such as snowy weather, negatively impacts the process and can hinder the regular operation of imaging equipment and the acquisition of conventional image information. Not only that, but the snow also makes intelligent transportation systems make the wrong judgment of road conditions and the entire system of the Internet of Vehicles adverse.… More > Graphic Abstract

    Single Image Desnow Based on Vision Transformer and Conditional Generative Adversarial Network for Internet of Vehicles

  • Open Access

    ARTICLE

    Container-Based Internet of Vehicles Edge Application Migration Mechanism

    Sujie Shao, Shihan Tian*, Shaoyong Guo, Xuesong Qiu

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4867-4891, 2023, DOI:10.32604/cmc.2023.038280

    Abstract Internet of Vehicles (IoV) applications integrating with edge computing will significantly drive the growth of IoV. However, the contradiction between the high-speed mobility of vehicles, the delay sensitivity of corresponding IoV applications and the limited coverage and resource capacity of distributed edge servers will pose challenges to the service continuity and stability of IoV applications. IoV application migration is a promising solution that can be supported by application containerization, a technology forseamless cross-edge-server application migration without user perception. Therefore, this paper proposes the container-based IoV edge application migration mechanism, consisting of three parts. The first is the migration trigger determination… More >

  • Open Access

    ARTICLE

    Secure Blockchain-Enabled Internet of Vehicles Scheme with Privacy Protection

    Jiansheng Zhang1, Yang Xin1,*, Yuyan Wang2, Xiaohui Lei2, Yixian Yang1

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6185-6199, 2023, DOI:10.32604/cmc.2023.038029

    Abstract The car-hailing platform based on Internet of Vehicles (IoV) technology greatly facilitates passengers’ daily car-hailing, enabling drivers to obtain orders more efficiently and obtain more significant benefits. However, to match the driver closest to the passenger, it is often necessary to process the location information of the passenger and driver, which poses a considerable threat to privacy disclosure to the passenger and driver. Targeting these issues, in this paper, by combining blockchain and Paillier homomorphic encryption algorithm, we design a secure blockchain-enabled IoV scheme with privacy protection for online car-hailing. In this scheme, firstly, we propose an encryption scheme based… More >

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