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  • Open Access

    ARTICLE

    Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks

    Fei Li1, *, Jiayan Zhang1, Edward Szczerbicki2, Jiaqi Song1, Ruxiang Li 1, Renhong Diao1

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 653-681, 2020, DOI:10.32604/cmc.2020.011264 - 23 July 2020

    Abstract The increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated the intrusion detection system based on the in-vehicle system. We combined two algorithms to realize the efficient learning of the vehicle’s boundary behavior and the detection of intrusive behavior. In order to More >

  • Open Access

    ARTICLE

    Vehicle Target Detection Method Based on Improved SSD Model

    Guanghui Yu1, Honghui Fan1, Hongyan Zhou1, Tao Wu1, Hongjin Zhu1, *

    Journal on Artificial Intelligence, Vol.2, No.3, pp. 125-135, 2020, DOI:10.32604/jai.2020.010501 - 15 July 2020

    Abstract When we use traditional computer vision Inspection technology to locate the vehicles, we find that the results were unsatisfactory, because of the existence of diversified scenes and uncertainty. So, we present a new method based on improved SSD model. We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model. Meanwhile, the new method optimizes the loss function, such as the loss function of predicted offset, and makes the loss function drop more smoothly near zero points. In addition, the new method improves cross entropy More >

  • Open Access

    ARTICLE

    Behavioral Feature and Correlative Detection of Multiple Types of Node in the Internet of Vehicles

    Pengshou Xie1, Guoqiang Ma1, *, Tao Feng1, Yan Yan1, 2, Xueming Han1

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1127-1137, 2020, DOI:10.32604/cmc.2020.09695 - 10 June 2020

    Abstract Undoubtedly, uncooperative or malicious nodes threaten the safety of Internet of Vehicles (IoV) by destroying routing or data. To this end, some researchers have designed some node detection mechanisms and trust calculating algorithms based on some different feature parameters of IoV such as communication, data, energy, etc., to detect and evaluate vehicle nodes. However, it is difficult to effectively assess the trust level of a vehicle node only by message forwarding, data consistency, and energy sufficiency. In order to resolve these problems, a novel mechanism and a new trust calculating model is proposed in this… More >

  • Open Access

    ARTICLE

    Privacy Protection Algorithm for the Internet of Vehicles Based on Local Differential Privacy and Game Model

    Wenxi Han1, 2, Mingzhi Cheng3, *, Min Lei1, 2, Hanwen Xu2, Yu Yang1, 2, Lei Qian4

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1025-1038, 2020, DOI:10.32604/cmc.2020.09815 - 10 June 2020

    Abstract In recent years, with the continuous advancement of the intelligent process of the Internet of Vehicles (IoV), the problem of privacy leakage in IoV has become increasingly prominent. The research on the privacy protection of the IoV has become the focus of the society. This paper analyzes the advantages and disadvantages of the existing location privacy protection system structure and algorithms, proposes a privacy protection system structure based on untrusted data collection server, and designs a vehicle location acquisition algorithm based on a local differential privacy and game model. The algorithm first meshes the road… More >

  • Open Access

    ARTICLE

    Authentication of Vehicles and Road Side Units in Intelligent Transportation System

    Muhammad Waqas1, 2, Shanshan Tu1, 3, *, Sadaqat Ur Rehman1, Zahid Halim2, Sajid Anwar2, Ghulam Abbas2, Ziaul Haq Abbas4, Obaid Ur Rehman5

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 359-371, 2020, DOI:10.32604/cmc.2020.09821 - 20 May 2020

    Abstract Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents, economically damaging traffic jams, hijacking, motivating to wrong routes, and financial losses for businesses and governments. Smart and autonomous vehicles are connected wirelessly, which are more attracted for attackers due to the open nature of wireless communication. One of the problems is the rogue attack, in which the attacker pretends to be a legitimate user or access point by utilizing fake identity. To figure out the problem of a rogue attack, we propose a reinforcement learning algorithm to identify rogue nodes More >

  • Open Access

    ARTICLE

    Beam Approximation for Dynamic Analysis of Launch Vehicles Modelled as Stiffened Cylindrical Shells

    Siyang Piao1, Huajiang Ouyang1, 2, Yahui Zhang1, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 571-591, 2020, DOI:10.32604/cmes.2020.08789 - 01 February 2020

    Abstract A beam approximation method for dynamic analysis of launch vehicles modelled as stiffened cylindrical shells is proposed. Firstly, an initial beam model of the stiffened cylindrical shell is established based on the cross-sectional area equivalence principle that represents the shell skin and its longitudinal ribs as a beam with annular cross-section, and the circumferential ribs as lumped masses at the nodes of the beam elements. Then, a fine finite element model (FE model) of the stiffened cylindrical shell is constructed and a modal analysis is carried out. Finally, the initial beam model is improved through… More >

  • Open Access

    ARTICLE

    Dynamic Task Assignment for Multi-AUV Cooperative Hunting

    Xiang Cao1,2,3, Haichun Yu1,3, Hongbing Sun1,3

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 25-34, 2019, DOI:10.31209/2018.100000038

    Abstract For cooperative hunting by a multi-AUV (multiple autonomous underwater vehicles) team, not only basic problems such as path planning and collision avoidance should be considered but also task assignments in a dynamic way. In this paper, an integrated algorithm is proposed by combining the self-organizing map (SOM) neural network and the Glasius Bio-Inspired Neural Network (GBNN) approach to improve the efficiency of multi-AUV cooperative hunting. With this integrated algorithm, the SOM neural network is adopted for dynamic allocation, while the GBNN is employed for path planning. It deals with various situations for single/multiple target(s) hunting More >

  • Open Access

    ARTICLE

    A Novel SINS/IUSBL Integration Navigation Strategy for Underwater Vehicles

    Jian Wang1, Tao Zhang1,*, Bonan Jin1, Shaoen Wu2

    Journal of Cyber Security, Vol.1, No.1, pp. 1-10, 2019, DOI:10.32604/jcs.2019.05818

    Abstract This paper presents a novel SINS/IUSBL integration navigation strategy for underwater vehicles. Based on the principle of inverted USBL (IUSBL), a SINS/IUSBL integration navigation system is established, where the USBL device and the SINS are both rigidly mounted onboard the underwater vehicle, and fully developed in-house, the integration navigation system will be able to provide the absolute position of the underwater vehicle with a transponder deployed at a known position beforehand. Furthermore, the state error equation and the measurement equation of SINS/IUSBL integration navigation system are derived, the difference between the position calculated by SINS More >

  • Open Access

    ARTICLE

    A Data Download Method from RSUs Using Fog Computing in Connected Vehicles

    Dae-Young Kim1, Seokhoon Kim2,*

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 375-387, 2019, DOI:10.32604/cmc.2019.06077

    Abstract Communication is important for providing intelligent services in connected vehicles. Vehicles must be able to communicate with different places and exchange information while driving. For service operation, connected vehicles frequently attempt to download large amounts of data. They can request data downloading to a road side unit (RSU), which provides infrastructure for connected vehicles. The RSU is a data bottleneck in a transportation system because data traffic is concentrated on the RSU. Therefore, it is not appropriate for a connected vehicle to always attempt a high speed download from the RSU. If the mobile network… More >

  • Open Access

    ARTICLE

    Design of Working Model of Steering, Accelerating and Braking Control for Autonomous Parking Vehicle

    P. K. Shyamshankar1, S. Rajendraboopathy2, R. S. Bhuvaneswaran1,*

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 55-68, 2019, DOI:10.32604/cmc.2019.07761

    Abstract Now a days, the number of vehicles especially cars are increased day by day and the people expect sophistication with safety and they wish automation for the perfection by reducing their effort and to prevent damage from collision of the vehicle. Parking the vehicle has always been a big task for the drivers that lead to problems such as traffic, congestion, accident, pollution etc. In order to overcome the parking problem, an automatic steering, braking and accelerating system is proposed to park a vehicle in a stipulated area and also to enhance the parking in… More >

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