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Phishing is an online criminal act that occurs when a malicious webpage impersonates as legitimate webpage so as to acquire sensitive information from the user. Phishing attacks continue to pose a serious risk for web users and is an annoying threat within the field of electronic commerce. This book focuses on discerning the significant features that discriminate between legitimate and phishing URLs. These features are then subjected to data mining algorithms. The rules obtained are interpreted to emphasize the features that are more prevalent in phishing URLs. Analyzing the knowledge accessible on phishing URL and considering confidence as an indicator, the features like lexical features in the URL and keyword within the path portion of the URL were found to be sensible indicators for phishing URL. In addition to this number of slashes in the URL, dot in the host portion of the URL and length of the URL are also the key factors for phishing URL. We have achieved the detection rate of 90%, FPR is of 0.002%, FNR of 0.03% on our binary dataset.