Securing Financial XML Transactions Using Intelligent Fuzzy Classification Techniques

Abstract

The eXtensible Markup Language (XML) has been widely adopted in many financial institutions in their daily transactions. This adoption was due to the flexible nature of XML providing a common syntax for systems messaging in general and in financial messaging in specific. Excessive use of XML in financial transactions messaging created an aligned interest in security protocols integrated into XML solutions in order to protect exchanged XML messages in an efficient yet powerful mechanism. However, financial institutions (i.e. banks) perform large volume of transactions on daily basis which require securing XML messages on large scale. Securing large volume of messages will result performance and resource issues. Therefore, an approach is needed to secure specified portions of an XML document, syntax and processing rules for representing secured parts. In this research we have developed a smart approach for securing financial XML transactions using effective and intelligent fuzzy classification techniques. Our approach defines the process of classifying XML content using a set of fuzzy variables. Upon fuzzy classification phase, a unique value is assigned to a defined attribute named “Importance Level”. Assigned value indicates the data sensitivity for each XML tag. The research also defines the process of securing classified financial XML message content by performing element-wise XML encryption on selected parts defined in fuzzy classification phase. Element-wise encryption is performed using symmetric encryption using AES algorithm with different key sizes. Key size of 128-bit is being used on tags classified with “Medium” importance level; a key size of 256-bit is being used on tags classified with “High” importance level. An implementation has been performed on a real-life environment using online banking system in Jordan Ahli Bank one of the leading banks in Jordan to demonstrate its flexibility, feasibility, and efficiency. Our experimental results of the system verified tangible enhancements in encryption efficiency, processing-time reduction, and resulting XML message sizes. Finally, our proposed system was designed, developed, and evaluated using a live data extracted from an internet banking service in one of the leading banks in Jordan. The results obtained from our experiments are promising, showing that our model can provide an effective yet resilient support for financial systems to secure exchanged financial XML messages.