Empirical study of online hybrid model for internet frauds prevention and detection

Nowadays cyber forensics is the field which is dealing with several online fraudulent cases. Increase in internet practice is further enhancing the possibilities of online frauds. In our previous research we have proposed Online Hybrid Model (OHM) which prevents Online Auction, Non-Delivery/Merchandise, Card theft and Identity theft frauds. If prevention is not possible (or fraud occurs in in-auction process like collusive bidding, shill bidding or/and multiple bidding) then OHM further suggests fraud detection and elimination technique. Thus OHM is responsible to regularly monitor interaction between users and web servers. In this paper we have elaborated the requirement engineering and working of various OHM modules. We have shown the robustness of these modules in terms of logical design and their operational interaction. Furthermore, we have evaluated the performance of this model and have shown that OHM is highly effective online fraud prevention/detection/elimination approach.