IoT anomaly detection method in intelligent manufacturing industry based on trusted evaluation

被引:0
|
作者
Chao Wang
机构
[1] Southwest Minzu University,Information and Educational Technology Center
关键词
Trusted assessment; Industrial Internet of Things; Trusted routing; Anomaly detection;
D O I
暂无
中图分类号
学科分类号
摘要
With the development of industrial Internet of Things technology, the relatively closed industrial control system has become more complex and open, and it is facing increasingly serious information security problems. Aiming at the security problems existing in the current intelligent manufacturing industrial Internet of Things, this paper proposes a credible overall architecture of the IoT industrial control system. By adding a trusted function module, the credibility level is evaluated and abnormal operations are monitored. The sensing environment for the Internet of Things is more complicated. This paper proposes a cluster-based routing method. While ensuring the trustworthiness and security of data routing, the routing protocol is maintained efficiently and reliably. A scenario of node cooperation is proposed for scenarios of a large number of malicious nodes. Abnormal attacks are suppressed by maintaining dynamic Bayesian balance between the attacker and the detection node. The simulation results show that the mechanism cooperation game can significantly improve the event detection success rate of abnormal detection nodes and greatly reduce the number of forged reports.
引用
收藏
页码:993 / 1005
页数:12
相关论文
共 50 条
  • [41] Improving Method of Anomaly Detection Performance for Industrial IoT Environment
    Kim, Junwon
    Shin, Jiho
    Park, Ki-Woong
    Seo, Jung Taek
    CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 72 (03): : 5377 - 5394
  • [42] A graph neural network method for distributed anomaly detection in IoT
    Aikaterini Protogerou
    Stavros Papadopoulos
    Anastasios Drosou
    Dimitrios Tzovaras
    Ioannis Refanidis
    Evolving Systems, 2021, 12 : 19 - 36
  • [43] The Platform of Intelligent Manufacturing System Based on Industry 4.0
    Yang, Jinghui
    Huang, Guorong
    Hang, Qi
    ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: PRODUCTION MANAGEMENT FOR DATA-DRIVEN, INTELLIGENT, COLLABORATIVE, AND SUSTAINABLE MANUFACTURING, APMS 2018, 2018, 535 : 350 - 354
  • [44] IoT-Based Intelligent Perception and Access of Manufacturing Resource Toward Cloud Manufacturing
    Tao, Fei
    Zuo, Ying
    Xu, Li Da
    Zhang, Lin
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2014, 10 (02) : 1547 - 1557
  • [45] Anomaly Detection Model Based Visual Inspection Method for PCB Board Manufacturing Process
    Lee, Sang-Jeong
    Seo, Sung-Bal
    Bae, You-Suk
    Transactions of the Korean Institute of Electrical Engineers, 2024, 73 (11): : 2024 - 2029
  • [46] Dynamic cost evaluation method of intelligent manufacturing enterprises based on DEA model
    Mo Z.
    Zhao C.
    International Journal of Manufacturing Technology and Management, 2021, 35 (03) : 181 - 199
  • [47] Administrative Management Data Anomaly Access Detection Method, Based on 6G IoT
    Tu, Yangmin
    Zou, Tao
    WIRELESS PERSONAL COMMUNICATIONS, 2024,
  • [48] An IoT Environment Based Framework for Intelligent Intrusion Detection
    Safwan, Hamza
    Iqbal, Zeshan
    Amin, Rashid
    Khan, Muhammad Attique
    Alhaisoni, Majed
    Alqahtani, Abdullah
    Kim, Ye Jin
    Chang, Byoungchol
    CMC-COMPUTERS MATERIALS & CONTINUA, 2023, 75 (02): : 2365 - 2381
  • [49] Anomaly detection based on intelligent techniques over a bicomponent production plant used on wind generator blades manufacturing
    Jove, E.
    Casteleiro-Roca, J.
    Quintian, H.
    Mendez-Perez, J. A.
    Calvo-Rolle, J. L.
    REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL, 2020, 17 (01): : 84 - 93
  • [50] Image anomaly detection for IoT equipment based on deep learning
    Hou Rui
    Pan MingMing
    Zhao YunHao
    Yang Yang
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2019, 64