Muhammad Shahzad Haroon*, Husnain Mansoor Ali
CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3513-3527, 2022, DOI:10.32604/cmc.2022.029858
Abstract Intrusion detection system plays an important role in defending networks from security breaches. End-to-end machine learning-based intrusion detection systems are being used to achieve high detection accuracy. However, in case of adversarial attacks, that cause misclassification by introducing imperceptible perturbation on input samples, performance of machine learning-based intrusion detection systems is greatly affected. Though such problems have widely been discussed in image processing domain, very few studies have investigated network intrusion detection systems and proposed corresponding defence. In this paper, we attempt to fill this gap by using adversarial attacks on standard intrusion detection datasets and then using adversarial samples… More >
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