Behaviour-Based Attack Detection and Classification in Cyber Physical Systems Using Machine Learning
Author:
Affiliation:
1. Singapore University of Technology and Design;Karachi Institute of Economics and Technology, Pakistan, Singapore, Singapore
2. Singapore University of Technology and Design, Singapore, Singapore
Funder
National Research Foundation (NRF), Prime Minister's Office, Singapore
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2899015.2899016
Reference36 articles.
1. Nsl-kdd dataset 2006. Nsl-kdd dataset 2006.
2. An Investigation into the Response of a Water Treatment System to Cyber Attacks
3. Enhancing SVM performance in intrusion detection using optimal feature subset selection based on genetic principal components
4. O. Al-Jarrah and A. Arafat. Network intrusion detection system using neural network classification of attack behavior. Journal of Advances in Information Technology Vol 6(1) 2015. O. Al-Jarrah and A. Arafat. Network intrusion detection system using neural network classification of attack behavior. Journal of Advances in Information Technology Vol 6(1) 2015.
5. Specification-Based Intrusion Detection for Advanced Metering Infrastructures
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