Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization

by   Rana Abou Khamis, et al.

With the growth of adversarial attacks against machine learning models, several concerns have emerged about potential vulnerabilities in designing deep neural network-based intrusion detection systems (IDS). In this paper, we study the resilience of deep learning-based intrusion detection systems against adversarial attacks. We apply the min-max (or saddle-point) approach to train intrusion detection systems against adversarial attack samples in NSW-NB 15 dataset. We have the max approach for generating adversarial samples that achieves maximum loss and attack deep neural networks. On the other side, we utilize the existing min approach [2] [9] as a defense strategy to optimize intrusion detection systems that minimize the loss of the incorporated adversarial samples during the adversarial training. We study and measure the effectiveness of the adversarial attack methods as well as the resistance of the adversarially trained models against such attacks. We find that the adversarial attack methods that were designed in binary domains can be used in continuous domains and exhibit different misclassification levels. We finally show that principal component analysis (PCA) based feature reduction can boost the robustness in intrusion detection system (IDS) using a deep neural network (DNN).


Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs

Network security applications, including intrusion detection systems of ...

Adversarial Attacks on Machine Learning Cybersecurity Defences in Industrial Control Systems

The proliferation and application of machine learning based Intrusion De...

A Novel Deep Learning based Model to Defend Network Intrusion Detection System against Adversarial Attacks

Network Intrusion Detection System (NIDS) is an essential tool in securi...

TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems

Nowadays, intrusion detection systems based on deep learning deliver sta...

On the Resilience of Machine Learning-Based IDS for Automotive Networks

Modern automotive functions are controlled by a large number of small co...

A cognitive based Intrusion detection system

Intrusion detection is one of the primary mechanisms to provide computer...

Please sign up or login with your details

Forgot password? Click here to reset