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Studying the Fuzzy clustering algorithm for intrusion detection on the attacks to the Domain Name System | IEEE Conference Publication | IEEE Xplore

Studying the Fuzzy clustering algorithm for intrusion detection on the attacks to the Domain Name System


Abstract:

It is undeniable that cybersecurity systems play an important role in our modern computer systems. The intrusion detection system is a core component of modern cybersecur...Show More

Abstract:

It is undeniable that cybersecurity systems play an important role in our modern computer systems. The intrusion detection system is a core component of modern cybersecurity systems. The task of an intrusion detection system is to detect anomalies in the incoming traffic then stop them before they can enter the internal system. In recent years, intrusion detection systems have been powered by the latest machine learning algorithms to increase the predictive performance. However, there is not yet the desired attention level of applying fuzzy techniques to empower the intrusion detection systems. In this paper, we study the usage of fuzzy clustering in the intrusion detection problem. We evaluated the algorithm using the state-of-the-art intrusion dataset. The results allow us to claim the potential of the fuzzy clustering algorithm for cybersecurity applications.
Date of Conference: 29-30 July 2021
Date Added to IEEE Xplore: 19 August 2021
ISBN Information:
Conference Location: London, United Kingdom

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