
Phishing has become the most popular practice among the criminals of the Web. Phishing attacks are becoming more frequent and sophisticated. The impact of phishing is drastic and significant since it can involve the risk of identity theft and financial losses. This paper explains the most popular methods used for phishing and the PhishCatch algorithm developed to detect phishing. The PhishCatch algorithm is a heuristic based algorithm which will detect phishing emails and alert the users about the phishing emails. The phishing filters and rules in the algorithm are formulated after extensive research of phishing methodologies and tactics. After testing, we determined that PhishCatch algorithm has a catch rate of 80% and an accuracy of 99%. The approach used in developing this algorithm, the implementation details and testing results are discussed in this paper.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 30 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
