Deep Feature Extraction for multi-Class Intrusion Detection in Industrial Control Systems
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[1] Dumitru Erhan,et al. Deep Neural Networks for Object Detection , 2013, NIPS.
[2] John McHugh,et al. Testing Intrusion detection systems: a critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by Lincoln Laboratory , 2000, TSEC.
[3] A. Malathi,et al. A Detailed Analysis on NSL-KDD Dataset Using Various Machine Learning Techniques for Intrusion Detection , 2013 .
[4] Dhruba Kumar Bhattacharyya,et al. Network Anomaly Identification using Supervised Classifier , 2013, Informatica.
[5] S. P. Shantharajah,et al. A Study on NSL-KDD Dataset for Intrusion Detection System Based on Classification Algorithms , 2015 .
[6] Pieter H. Hartel,et al. Challenges and opportunities in securing industrial control systems , 2012, 2012 Complexity in Engineering (COMPENG). Proceedings.
[7] Morteza Amini,et al. RT-UNNID: A practical solution to real-time network-based intrusion detection using unsupervised neural networks , 2006, Comput. Secur..
[8] Rowayda A. Sadek,et al. Effective Anomaly Intrusion Detection System based on Neural Network with Indicator Variable and Rou , 2013 .
[9] Deeman Yousif Mahmood,et al. Feature Based Unsupervised Intrusion Detection , 2014 .
[10] Md Zahangir Alom,et al. Intrusion detection using deep belief networks , 2015, 2015 National Aerospace and Electronics Conference (NAECON).