PeANFIS-FARM Framework in defending against Web Service attacks

Chan, Gaik-Yee and Lee, Chien-Sing and Heng, Swee-Huay (2013) PeANFIS-FARM Framework in defending against Web Service attacks. Advances in Intelligent Systems Research. pp. 108-112. ISSN 1951-6851

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Abstract

Internet-enabled Web Service (WS) applications, such as e-commerce, are facing eXtensible Markup Language (XML)-related security threats. However, network and host-based intrusion (ID) and prevention (IP) systems and Web Service Security (WSS) standards are inadequate in countering against these threats. This paper presents a framework to mitigate XML/SOAP attacks. Our framework comprises of two intelligent models: the policy-enhanced adaptive neuro-fuzzy inference system (PeANFIS) and fuzzy association rule mining (FARM) model. Performance evaluation of each model indicates detection rate of greater than 99% and false alarm rate of less than 1%. In this paper, we aim to help the security administrator to decide which model to implement depending on the context of the situation. We present rule-based cases as examples to guide design and implementation decisions. Our future work shall see the implementation of the PeANFIS-FARM framework on a wider scale and in cloud computing.

Item Type: Article
Additional Information: International Workshop on Cloud Computing and Information Security (CCIS 2013)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 08 Jul 2014 08:38
Last Modified: 08 Jul 2014 08:38
URI: http://shdl.mmu.edu.my/id/eprint/5606

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