IDS Using Reinforcement Learning Automata for Preserving Security in Cloud Environment

Partha Ghosh, Meghna Bardhan, Nilabhra Roy Chowdhury and Santanu Phadikar
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Partha Ghosh: Netaji Subhash Engineering College, Kolkata, India & Maulana Abul Kalam Azad University of Technology, Kolkata, India
Meghna Bardhan: Netaji Subhash Engineering College, Kolkata, India
Nilabhra Roy Chowdhury: Netaji Subhash Engineering College, Kolkata, India
Santanu Phadikar: Maulana Abul Kalam Azad University of Technology, Kolkata, India

International Journal of Information System Modeling and Design (IJISMD), 2017, vol. 8, issue 4, 21-37

Abstract: Cloud computing relies on sharing computing resources. With high availability and accessibility of resources, cloud computing is under the threat of major cyber-attacks. To detect attacks and preserve security in cloud environment, having an efficient intrusion detection system (IDS) is required. In this article, an effective and efficient IDS is proposed to maintain high level security of data in cloud. The authors have incorporated Reinforcement Learning Automata with their proposed IDS while detecting and classifying attacks. Using learning automata an effective rule set is generated with the proposed algorithm from vast training set to improve the learning process at reduced computation cost and time. After which, the proposed reinforcement learning algorithm helps in classification of attacks accurately using the reinforcement signal. This proposed model was experimented with NSL-KDD as well as KDD 10% dataset and have proved its robustness by detecting attacks more accurately being an IDS.

Date: 2017
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