Files

PDF

HOW TO CITE

Quantum Machine Learning Based Network IDS for DDoS Attack Detection in IoT: A Novel Approach
Authors (Affiliation): BIKRAM BIKASH DAS (School of Sciences, Woxsen University, Hyderabad 502345)
Abstract:

A Hybrid Classical Quantum Machine Learning (QML) Model for Mitigating and identifying Distributed Denial of Service (DDoS) Detection is a cutting-edge approach that combines classical machine learning techniques with quantum computing to enhance the performance of detecting such attack with more efficiently and precise accuracy rate with reduced false positive. The primacy concern for this paper is to investigate some of the current research challenges for mitigating Distributed Denial of Service (DDoS) for IoT based network. It becomes very difficult to identify the signature of such attack due to the huge volume of user request traffic for the target machine [1] .This Paper has outlined the detection of Distributed Denial of Service attack that can be performed by Quantum computer along with the Machine Learning techniques and also provided study of various existing research for the same. This paper also proposed a Hybrid Classical Quantum Machine learning Model for mitigating with such attack for future.

Keywords: IoT, Quantum Computing, DDoS Attack, Quantum Machine Learning (QML), Intrusion Detection Systems (IDS)
Vol & Issue: Special Issue - 1 (The Proceeding of ICRBDC - 2024), February 2024