A Novel Web Fraud Detection Technique using Association Rule Mining
Diwakar Tripathi, Bhawana Nigam, Damodar Reddy Edla · Procedia Computer Science · 2017
In the present scenario online web advertising is premier source of revenue for many internet web applications. Phishing is an activity of misleading web users to fraudulent web sites which can be used to steal the sensitive information from internet. In this article, we introduce a new architecture for web fraud detection using Apriori algorithm for association rule mining and phish tank database in web advertising network. Extensive experiments are done on the proposed architecture with web access log and results obtained by proposed architecture in terms of accuracy, error rate, memory used and search time are encouraging.