Network-based Intrusion Detection System for Preventing the Cloud Computing Environment from Cyber-Attacks using Deep Learning Algorithms

Thombre, Shrikant Umakant (2022) Network-based Intrusion Detection System for Preventing the Cloud Computing Environment from Cyber-Attacks using Deep Learning Algorithms. Masters thesis, Dublin, National College of Ireland.

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Abstract

In the current era, cloud computing is considered the most widespread source of storage, computation and communication because of its reliability and considered a safe place to store user and business data. However, due to increase in the internet traffic, the chances of a malicious attack on the cloud networks have also increased. Therefore, providing security to such systems has become a thing of prominent significance. In this paper, we presented an Intrusion Detection System (IDS) for the cloud computing environment to detect any kind of network attacks. The major objective of this research is to process incoming data packets, which can accurately classify the Normal Traffic and Malicious attacks. Among the Malicious attacks, our system also should be able to detect the type of the attack, at the same time take/recommend appropriate action as per the type of attack. For accurate prediction of different types of attacks, in this research multiple deep learning models have been deployed and tested. After evaluating the performance of all the deep learning algorithms, it has been found that the LSTM model was correctly able to classify attack types with the highest accuracy score of 99% over the test data. Based on the LSTM model, a Web application for intrusion detection system has been developed, which is based on client-server architecture and can detect the network attack types and anomaly activities in the network system in real-time.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Tamara Malone
Date Deposited:	08 Dec 2022 15:46
Last Modified:	08 Mar 2023 14:24
URI:	https://norma.ncirl.ie/id/eprint/5984

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