Download Abstract - Compassion Software Solutions

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.
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