Phishing Fraud

To this day, whenever we talk about internet vandalism, remind us viruses, worms, hackers, etc. Today a technique can be introduced which is used to cheat naïve users. Phishing can be an Abbreviation of Password Harvesting Fishing. Phishing is a social engineering crime which Uses impersonation and playing another role to obtain personal information (Whittaker et al, 2010). Damage caused by phishing includes Loss of an Internet subscription to empty bank account. In total it is costly for victims. First victim was a Internet Service Providing Company: AOL. On behalf of the company, some letters were sent to other victims cautioning them about multi-user use of their internet account.

Designed by ill-mannered individuals with the intention

The system included three layer containing six criteria every one of which comprises some indicators. The system analyses these indicators to match them with one of the three values namely Genuine, Doubtful and Fraud. Ultimately it is decided that the website fall into which of the five classes (“Very Legitimate”, “Legitimate”, “Suspicious”, “Phishy” and “Very Phishy”) (Aburrous et al, 2010). M.C.A.M. Phil and Valarmathi (2013) inserted three more indicators (Black list, iframe and Sloppy text) to the previous ones, thereby increasing number of indicators from 27 to

Based on the structure of ANFIS model(a hybrid technique with strengths of both Neural Networks and Fuzzy Logic) (Aburrous et al, 2010), as shown in figure 4 this layer has 8 nodes.Using Bell function the accuracy of this layer is calculated considering three premise parameters {ai , bi , ci} and x attribute that has the value between [0,1] to stimate μa(x) : (Singh et al,