Dr. Kamalakanta Sethi
Deep Reinforcement Learning based Intrusion Detection System for Cloud Infrastructure
1/1/2020
International Conference on COMmunication Systems & NETworkS (COMSNETS)
IEEE Explore
Abstract

Intrusion Detection in cloud platform is a challenging problem due to its extensive usage and distributed nature that are constant targets of new unknown attacks. detection system (IDS) responsible for monitoring detecting malicious activities any computing or network. However, most the traditional IDSs vulnerable novel Also, they incapable maintaining balance between high accuracy less false positive rate (FPR). In this paper, we propose deep reinforcement learning-based adaptive IDS architecture addresses above limitations performs accurate fine-grained classification complex We have done experimentation using benchmark UNSW-NB15 dataset shows better FPR compared state-of-the-art IDSs.

Keywords
Network Security and Intrusion DetectionAdvanced Malware Detection TechniquesInternet Traffic Analysis and Secure E-votingComputer Networks and CommunicationsSignal ProcessingArtificial Intelligence
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