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A Web Backtracking Technique for Fraud Detection in Financial Applications

A Web Backtracking Technique for Fraud Detection in Financial Applications

Tasawar Hussain, Sohail Asghar
Copyright: © 2018 |Pages: 18
ISBN13: 9781522534228|ISBN10: 1522534229|EISBN13: 9781522534235
DOI: 10.4018/978-1-5225-3422-8.ch037
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MLA

Hussain, Tasawar, and Sohail Asghar. "A Web Backtracking Technique for Fraud Detection in Financial Applications." Application Development and Design: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2018, pp. 861-878. https://doi.org/10.4018/978-1-5225-3422-8.ch037

APA

Hussain, T. & Asghar, S. (2018). A Web Backtracking Technique for Fraud Detection in Financial Applications. In I. Management Association (Ed.), Application Development and Design: Concepts, Methodologies, Tools, and Applications (pp. 861-878). IGI Global. https://doi.org/10.4018/978-1-5225-3422-8.ch037

Chicago

Hussain, Tasawar, and Sohail Asghar. "A Web Backtracking Technique for Fraud Detection in Financial Applications." In Application Development and Design: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 861-878. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-3422-8.ch037

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Abstract

The web based applications are maturing and gaining the confidence of their users gradually, however, www still lacks the mechanism to stop the hackers. The implementing the adhesive security measures such as intrusion deduction systems and firewalls, are no more useful breaker for online frauds. The Web Backtracking Technique (WBT) is proposed for fraud detection in online financial applications by applying the hierarchical sessionization technique on the web log file. The web log Hierarchical Sessionization enhances the focused groups of users from web log and paves the path for in-depth visualization for knowledge discovery. User clicks are compared with user profiles for change in previous user click records. Those transactions which do not conform to business rules are stopped from business activities. The WBT analyzes suspicious behavior and will produce reports for security and risk mitigation purposes Furthermore, suspicious transactions are mined for the up-gradation of business rules from hierarchical sessionization. The proposed WBT is validated against the university web log data.

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