Construction of customizable soa security framework using artificial neural networks

• Main Authors: Mohamed Ibrahim, M., Hassan, M.F.
• Format: Article
• Published: Penerbit UTM Press 2016
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006380028&doi=10.11113%2fjt.v78.10023&partnerID=40&md5=9fa6b7b024be28c3d63dfdb8fee931de; http://eprints.utp.edu.my/25879/

The Web Services technology for the implementation of Service Oriented Architecture (SOA) is the preferred choice in the current era of Enterprise Application Integration (EAI). As Web Services architecture is dynamic and loosely coupled, security aspects must be considered thoroughly at the time of designing. It is prone for attacks as it uses XML format for data exchange, which is a plain text. A novel security component named �Intelligent Security Engine (ISE)� is introduced into the proposed framework which incorporates Artificial Neural Networks (ANN) Learning Techniques for supervised knowledge acquisition on security threats of SOA. Thus, the proposed security framework is capable in the identification of future security vulnerabilities of SOA and can work effectively even for in-secured cross organizational EAI environment. © 2016 Penerbit UTM Press. All rights reserved.