Application and optimization of intrusion detection system based on Artificial Intelligence

被引:0
|
作者
Zhu, Kaidi [1 ]
Wu, Xiangwen [2 ]
Yu, Sun [3 ]
Huo, Da [4 ]
Li, Rui [1 ]
Pei, Xikai [1 ]
机构
[1] Second Res Inst CAAC, Chengdu, Peoples R China
[2] Inner Mongolia Autonomous Reg Civil Airports Grp, Hulun Buir Branch, Hulunbeir, Peoples R China
[3] North China Regionnal Air Traff Management Bur CA, Beijing, Peoples R China
[4] China Civilaviat Adm, Air Traff Management Bur, Beijing, Peoples R China
关键词
image processing; machine learning; Intrusion Detection Technology; Microwave array technology;
D O I
暂无
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The traditional perimeter intrusion detection system will be faced more challenges in the new era, such as high-accuracy positioning, low energy dependence, high environmental robustness and so on. This paper introduces a new type of artificial intelligence intrusion detection technology. The RF sensor chip is embedded in the detection cable, and the radio frequency electromagnetic environment is formed in space through the sending and receiving of radio frequency signal, which is used to sense the surrounding environment to detect electromagnetic field.Using advanced space-time signal processing technology and machine learning technology, the influence of environmental interference on the system is effectively eliminated, and the intrusion detection system based on artificial intelligence algorithm has lower false alarm rate and higher environmental robustness.
引用
收藏
页码:1053 / 1058
页数:6
相关论文
共 50 条
  • [1] An Artificial Intelligence-Based Intrusion Detection System using Optimization and Deep Learning
    Garapati, Satish Kumar
    Sigappi, A. N.
    [J]. JOURNAL OF ELECTRICAL SYSTEMS, 2024, 20 (06) : 1200 - 1217
  • [2] Explainable Artificial Intelligence for Intrusion Detection System
    Patil, Shruti
    Varadarajan, Vijayakumar
    Mazhar, Siddiqui Mohd
    Sahibzada, Abdulwodood
    Ahmed, Nihal
    Sinha, Onkar
    Kumar, Satish
    Shaw, Kailash
    Kotecha, Ketan
    [J]. ELECTRONICS, 2022, 11 (19)
  • [3] Design of a Lightweight Network Intrusion Detection System Based on Artificial Intelligence Technology
    He, Li
    [J]. Journal of Cyber Security and Mobility, 2024, 13 (05): : 1129 - 1148
  • [4] A NETWORK INTRUSION DETECTION SYSTEM BASED ON ARTIFICIAL INTELLIGENCE AND SEMANTIC WEB TECHNIQUES
    Zamfira, Andrei
    Ciocarlie, Horia
    [J]. ACTA TECHNICA NAPOCENSIS SERIES-APPLIED MATHEMATICS MECHANICS AND ENGINEERING, 2020, 63 (04): : 451 - 460
  • [5] Network intrusion detection system: A survey on artificial intelligence-based techniques
    Habeeb, Mohammed Sayeeduddin
    Babu, T. Ranga
    [J]. EXPERT SYSTEMS, 2022, 39 (09)
  • [6] Survey on Methodology of Intrusion Detection in Industrial Control System Based on Artificial Intelligence
    Li, Ligang
    Fu, Zhenyu
    Zou, Gaokai
    Mu, Zongjun
    Zhang, Qiaoxia
    Wang, Guangmin
    Wang, Pan
    [J]. 2022 INTERNATIONAL CONFERENCE ON COMPUTERS AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES, CAIT, 2022, : 93 - 103
  • [7] Network Intrusion Detection Based on Explainable Artificial Intelligence
    Wang, Yiwen
    Xu, Lei
    Liu, Wanli
    Li, Rongzhen
    Gu, Junjie
    [J]. WIRELESS PERSONAL COMMUNICATIONS, 2023, 131 (02) : 1115 - 1130
  • [8] Network Intrusion Detection Based on Explainable Artificial Intelligence
    Yiwen Wang
    Lei Xu
    Wanli Liu
    Rongzhen Li
    Junjie Gu
    [J]. Wireless Personal Communications, 2023, 131 : 1115 - 1130
  • [9] The Use of Artificial Intelligence for the Intrusion Detection System in Computer Networks
    Yip Ortuno, Santiago
    Hernandez Aguilar, Jose Alberto
    Taboada, Blanca
    Ochoa Ortiz, Carlos Alberto
    Perez Ramirez, Miguel
    Arroyo Figueroa, Gustavo
    [J]. ADVANCES IN SOFT COMPUTING, MICAI 2017, PT I, 2018, 10632 : 302 - 312
  • [10] Artificial intelligence approaches for intrusion detection
    Novikov, Dima
    Yampolskiy, Roman V.
    Reznik, Leon
    [J]. 2006 IEEE LONG ISLAND SYSTEMS, APPLICATIONS AND TECHNOLOGY CONFERENCE, 2006, : 23 - +