PeANFIS-FARM for discovering rules for XML intrusion detection and prevention

Chan, Gaik Yee (2012) PeANFIS-FARM for discovering rules for XML intrusion detection and prevention. PhD thesis, Multimedia University.

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Abstract

The Internet and XML-based Web Services (WS) have revolutionised the Information Technology industry. Increasing number of software applications, especially Business Intelligence (BI) or e-commerce applications are built on this Internet and Web service-enabled platform. Consequently, the Application Layer is open to various types of XML-related threats. Although active research has been ongoing in host-based and network-based intrusion detection (ID) and intrusion prevention (IP) areas, they are not adequate to address the problems or countermeasure the attacks occurring at the Application Layer. These ID/IP systems merely detect attacks by observing various network and host’s activities, but do not address XML-related attacks. Even though basic standards such as XML Digital Signature and XML Encryption exist, they are still not adequate to address the security threats and vulnerabilities completely. For example, XML Encryption can mask message content being inspected, thus concealing probable attacks such as oversized payload, coercive parsing or XML injection. In view of the XML-related security threats, this study has developed an adaptive ID/IP framework incorporated with predictive fuzzy models that validate inputs and SOAP size to counter XML-related attacks.

Item Type: Thesis (PhD)
Additional Information: Call No.: TK5105.59 C43 2012
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: 27 Mar 2014 02:29
Last Modified: 27 Mar 2014 02:29
URI: http://shdl.mmu.edu.my/id/eprint/5402

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