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MNSSA: Meso-level Network Security Situation Awareness for ICS via Graph Evolution Analysis

  • Shilong Zhang
  • , Hui Zhang
  • , Guo Chen
  • , He Luo
  • , Meiqi Wu
  • , Hongxiang Chen
  • , Zehua Ren
  • , Zijun Wang
  • , Yang Liu
  • Xi'an Jiaotong University
  • Digital Management Center
  • Polytechnic University of Milan

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Intrusion detection systems (IDSs) are widely used for generating alarms indicating potential network security risks based on network traffic monitoring in industrial control systems (ICSs). However, it is a big burden for security analysts to handle numerous alarms in real time. Also, most alarms are falsely triggered by normal operations, which makes the real attack risks hard to find. In this paper, we propose MNSSA, a meso-level network security situation awareness method that conducts graph evolution analysis on the ICS alarms. MNSSA can semi-automatically filter low-risk false alarms in bulk and detect attack events. It can better analyze the network security situation and improve alarm processing efficiency.

源语言英语
主期刊名2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024
出版商IEEE Computer Society
3628-3634
页数7
ISBN(电子版)9798350358513
DOI
出版状态已出版 - 2024
活动20th IEEE International Conference on Automation Science and Engineering, CASE 2024 - Bari, 意大利
期限: 28 8月 20241 9月 2024

出版系列

姓名IEEE International Conference on Automation Science and Engineering
ISSN(印刷版)2161-8070
ISSN(电子版)2161-8089

会议

会议20th IEEE International Conference on Automation Science and Engineering, CASE 2024
国家/地区意大利
Bari
时期28/08/241/09/24

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