Efficient Intrusion Detection system in Cloud Computing environment using Deep Learning Algorithms

Ponnada, Vishnu Vardhan (2023) Efficient Intrusion Detection system in Cloud Computing environment using Deep Learning Algorithms. Masters thesis, Dublin, National College of Ireland.

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Abstract

As the digital landscape evolves, the challenges faced by network specialists in the realm of cloud communication and information intensify. The critical concern revolves around detecting malicious behaviors originating from individual hosts and spreading across interconnected cloud networks. Intrusions, representing unauthorized breaches within cloud resources, have catalyzed the demand for efficient Intrusion Detection Systems (IDS). Administrations and organizations have turned to creative remedies to counter these risks, and one particularly promising strategy is the employment of deep neural network algorithms. The current research focuses on applying deep learning algorithms to identify and categorize various security attacks in the cloud computing environment. A possible address is provided by deep learning, which is recognized for its capacity to uncover complicated patterns within big datasets. Several algorithms were used in this work Among tested models, the Autoencoder displayed superior performance, exhibiting an accuracy of 99.56% in identifying and categorizing malicious and Benign attacks within cloud environments. Further enhancing the study’s contribution to cloud security, a real-time web application has been developed using Flask. This application adeptly detects security threats by meticulously analyzing network packets in real-time. The findings of this study contribute significantly to the realm of cloud security, furnishing valuable insights and establishing a robust framework for enhancing threat detection and mitigation tactics within cloud environments.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Kazmi, Aqeel UNSPECIFIED
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:	18 Oct 2024 15:48
Last Modified:	18 Oct 2024 15:48
URI:	https://norma.ncirl.ie/id/eprint/7100

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