Please use this identifier to cite or link to this item: http://ddms.usim.edu.my:80/jspui/handle/123456789/8502
Title: A systematic analysis on worm detection in cloud based systems
Authors: H.M., Kanaker
M.M., Saudi
M.F., Marhusin
Keywords: Cloud computing
Genetic algorithm
Intrusions detection
Worms
Issue Date: 2015
Publisher: Asian Research Publishing Network
Abstract: An innovative breakthrough in computer science is cloud computing and involves several computers which are connected via the Internet or it is dispersed over a network. A large database, services, applications, software and resources are an integral part of this technology. It has the capability to operate a program or applications on numerous connected computers simultaneously and permits the users to enter applications and resources through a web browser or web service via the Internet anytime and anywhere. Current susceptibility in elementary technologies gravitates to expose doors for intrusions. Cloud computing offers enormous advantages such as cost reduction, dynamic virtualized resources, significant data storage and enhanced productivity. At the same time, numerous risks occur regarding security and intrusions, for example, worm can intercept cloud computing services, impair service, application or virtual in the cloud formation. Worm attacks are now more complex and resourceful making intruders more difficult to detect than previously. The motivation of this research is founded on ramifications presented bythe worms. This paper presents different intrusion detection systems affecting cloud resources and service. Moreover, this paper illustrates how genetic algorithm can be integrated in detecting worm attacks in cloud computing more efficiently.
URI: http://ddms.usim.edu.my/handle/123456789/8502
http://www.arpnjournals.com/jeas/research_papers/rp_2015/jeas_0215_1488.pdf
ISSN: 1819-6608
Appears in Collections:ARPN Journal of Engineering and Applied Sciences

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