Improved Banking XML Transaction Encryption Using Tag Fuzzy Classification

In this paper we present a novel approach for securing financial XML transactions using intelligent fuzzy classification techniques. Given an XML message X, our approach defines the process of classifying XML content to assign a unique value, which indicates the data sensitivity declaring importance level for each XML tag. The classified message Xs includes this new modified attributes with importance level value assigned for each tag. The framework also defines the process of securing classified financial XML message by performing element-wise XML encryption on selected parts defined in Xs. Based on our approach, we define which encryption algorithm is more appropriate to be deployed on selected parts depending on importance level attribute defined in Xs.
An implementation has been performed on a real life environment using online banking systems to demonstrate its flexibility, feasibility, and security. Our experimental results of the new model verified tangible enhancements in encryption efficiency, processing time reduction, and financial XML message utilization.