Active Defense Technology of Power Monitoring System With Adaptive Features

Liu, Wei; Yao, Yiyang; Zhao, Baohua; Yang, Weiyong; Qi, Longyun; Lv, Xiaoliang

doi:10.1109/access.2018.2870116

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…The literature 2 designed a comprehensive cybersecurity architecture and discussed the functions of each part in this architecture. The literature 3 proposed a TMAC model based on trusted mandatory access control, thus building a security immunity and active defense system for power monitoring systems. The literature 4 proposes a comprehensive active defense system framework by implementing appropriate defenses in host, security, and network devices.…”

Section: Introductionmentioning

confidence: 99%

Snort3-based wind farm behavioral characteristic inspector design

Jin,

Lin,

et al. 2023

Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023)

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Due to the increasingly complex network environment, wind farm power monitoring systems are more and more likely to be exposed to vulnerabilities. Intrusion detection, as an important supplement to firewalls, can detect anomalies and effectively defend against network attacks. In this paper, a normal behavior feature model is constructed, and then rules are configured for Snort3. Finally, a Snort3-based wind farm behavioral characteristic inspector is designed based on the normal behavioral characteristic model and Snort3 rule configuration to detect unknown anomalous messages. The ability of the inspector to extract behavioral characteristics and detect anomalous messages was verified through experiments. The results show that the inspector can effectively detect data tampering attacks and man-in-the-middle attacks with reasonableness and effectiveness.

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Section: Introductionmentioning

confidence: 99%