Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/57286
Title: Efficient approaches for intrusion detection in cloud environment
Contributor(s): Mishra, Preeti (author); Pilli, Emmanuel S (author); Varadharajan, Vijay (author); Tupakula, Udaya  (author)orcid 
Publication Date: 2016
DOI: 10.1109/CCAA.2016.7813926
Handle Link: https://hdl.handle.net/1959.11/57286
Abstract: 

Intrusion Detection System is one of the challenging research areas in Cloud Security. Security incidents such as Denial of service, scanning, malware code injection, virus, worm and password cracking are becoming common in cloud environment. These attacks can become a threat to the reputation of the company and can also cause financial loss if not detected on time. Hence securing the cloud from these types of attacks is very important. In this paper, we have proposed techniques to secure cloud environment by incorporating some of the efficient approaches in intrusion detection. We have focused on two major issues in IDS: efficient detection mechanism and speed of detection. We have proposed approaches to tackle these issues using Machine Learning and parallelization. We have also provided security frameworks to demonstrate how these approaches will be deployed in Cloud Environment. A preliminary analysis was conducted for some of the approaches and results are promising.

Publication Type: Conference Publication
Conference Details: 2016 International Conference on Computing, Communication and Automation (ICCCA), Greater Noida, India, 29th - 30th April, 2016
Source of Publication: Proceeding IEEE International Conference on Computing, Communication and Automation (ICCCA 2016), p. 1211-1216
Publisher: IEEE
Place of Publication: United States of America
Fields of Research (FoR) 2020: 460407 System and network security
Socio-Economic Objective (SEO) 2020: 220405 Cybersecurity
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

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