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Project Name : Phishing and Malware Site Categorization using Support Vector Machine Technology : Java , Sql Domain : Data Mining Abstract Malicious URLs have been widely used to mount various cyber attacks including spamming, phishing and malware. Phishing is a security attack that involves obtaining sensitive or otherwise private data by presenting oneself as a trustworthy entity. Phishes often exploit users’ trust on the appearance of a site by using web pages that are visually similar to an authentic site. Phishing is a significant problem involving fraudulent email and web sites that trick unsuspecting users into revealing private information. Most of the phishing attacks emerge as spoofed E-Mails appearing as legitimate ones which make the users to trust and divulge into them by clicking the link provided in the E-Mail. Detection of malicious URLs and identification of threat types are critical to thwart these attacks. Knowing the type of a threat enables estimation of severity of the attack and helps adopt an effective countermeasure. Detecting malicious URLs is an essential task in network security intelligence. In this paper we categories phishing and malware URLs using Support Vector Machine (SVM). Our method uses a variety of discriminative features including textual properties, link structures, webpage contents, DNS information, and network traffic. Our experiments show that our proposed method is good at detecting phishing and malware sites, correctly labeling approximately 95% of phishing and malware sites. We achieves high performance, including high level of true positive, true negative, sensitivity, precision, F-measure and overall accuracy compared with other approaches. Index Terms— Cluster ensemble, malware categorization, phishing website detection. Contact Us: F-303, Second Floor, Megacenter, Magarpatta chowk , Pune-solapur road, Hadapsar, Pune 9260528020 / 020 66200913 Mail us [email protected] www.compassionsoftwares.com