Early Detection of Cyber-Physical Attacks on Electric Vehicles Fast Charging Stations Using Wavelets and Deep Learning

被引:2
|
作者
Abu-Nassar, Ahmad M. [1 ]
Morsi, Walid G. [1 ]
机构
[1] Ontario Tech University (UOIT), Electrical, Computer and Software Engineering Department, Faculty of Engineering and Applied Science, Oshawa,ON,L1G 0C5, Canada
关键词
D O I
10.1109/TICPS.2024.3413605
中图分类号
学科分类号
摘要
引用
收藏
页码:220 / 231
相关论文
共 50 条
  • [21] An Ensemble Learning-Based Cyber-Attacks Detection Method of Cyber-Physical Power Systems
    Lu, Kang-Di
    Wu, Zheng-Guang
    2022 INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND MECHATRONICS (ICARM 2022), 2022, : 1029 - 1034
  • [22] Using Ensemble Learning for Anomaly Detection in Cyber-Physical Systems
    Jeffrey, Nicholas
    Tan, Qing
    Villar, Jose R.
    ELECTRONICS, 2024, 13 (07)
  • [23] VULNERABILITY DETECTION IN CYBER-PHYSICAL SYSTEM USING MACHINE LEARNING
    Bharathi, V
    Kumar, C. N. S. Vinoth
    SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2024, 25 (01): : 577 - 592
  • [24] Detection of Integrity Attacks in Cyber-Physical Critical Infrastructures Using Ensemble Modeling
    Ntalampiras, Stavros
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2015, 11 (01) : 104 - 111
  • [25] DECEPT: Detecting Cyber-Physical Attacks using Machine Learning on Log Data
    Skopik, Florian
    Wurzenberger, Markus
    Landauer, Max
    ERCIM NEWS, 2020, (123): : 33 - 34
  • [26] Boosting Cyberattack Detection Using Binary Metaheuristics With Deep Learning on Cyber-Physical System Environment
    Al Mazroa, Alanoud
    Albogamy, Fahad R.
    Khairi Ishak, Mohamad
    Mostafa, Samih M.
    IEEE ACCESS, 2025, 13 : 11280 - 11294
  • [27] Distribution Grid Impact of Plug-In Electric Vehicles Charging at Fast Charging Stations Using Stochastic Charging Model
    Yunus, Kalid
    De La Parra, Hector Zelaya
    Reza, Muhamad
    PROCEEDINGS OF THE 2011-14TH EUROPEAN CONFERENCE ON POWER ELECTRONICS AND APPLICATIONS (EPE 2011), 2011,
  • [28] INDUSTRIAL WIRELESS CYBER-PHYSICAL SYSTEMS PERFORMANCE USING DEEP LEARNING
    Kashef , Mohamed
    Candell, Richard
    Montgomery, Karl
    PROCEEDINGS OF ASME 2023 18TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, MSEC2023, VOL 2, 2023,
  • [29] DeepFed: Federated Deep Learning for Intrusion Detection in Industrial Cyber-Physical Systems
    Li, Beibei
    Wu, Yuhao
    Song, Jiarui
    Lu, Rongxing
    Li, Tao
    Zhao, Liang
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (08) : 5615 - 5624
  • [30] Deep Learning Based Attack Detection for Cyber-Physical System Cybersecurity: A Survey
    Jun Zhang
    Lei Pan
    Qing-Long Han
    Chao Chen
    Sheng Wen
    Yang Xiang
    IEEE/CAA Journal of Automatica Sinica, 2022, 9 (03) : 377 - 391