A systematic analysis on worm detection in cloud based systems

• Main Authors: H.M., Kanaker, M.M., Saudi, M.F., Marhusin
• Format: Article
• Language: en_US
• Published: Asian Research Publishing Network 2015
• Subjects: Cloud computing; Genetic algorithm; Intrusions detection; Worms
• Online Access: http://ddms.usim.edu.my/handle/123456789/8502; http://www.arpnjournals.com/jeas/research_papers/rp_2015/jeas_0215_1488.pdf

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.