Abstract:
The rapid advancement in internet has paved way for several serious crimes,
of which phishing occupies a very important place. Phishing is a form of cybercrime
where an attacker mimicking a legitimate website or a person or an organization redirects
the victims to steal confidential data through e-mail, malwares or some other social
engineering platforms. Victims prominently suffer from financial loss and private data
loss. The serious outbreak of phishing has paved way for many researches, though
comprehensive and accurate solution has not been proposed so far for thwarting its
impact. This paper aims to develop a resilient model to predict phishing scam by means
of classification algorithms of data mining. Five algorithms were chosen for this purpose
and a comparative study was undertaken for their performances, accuracy, error rate and
efficiency. The rules generated from the algorithms showed up a relatively better
performance than the existing phishing detection tools
