Feature-based phishing detection technique

• Main Authors: Xin, Mei Choo, Kang, Leng Chiew, Dayang Hanani, Abang Ibrahim, Nadianatra, Musa, San, Nah Sze, Wei, King Tiong
• Format: Article
• Language: English
• Published: Asian Research Publishing Network 2016
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/13943/7/FEATURE-BASED%20PHISHING%20DETECTION%20TECHNIQUE%20%28abstract%29.pdf; http://ir.unimas.my/id/eprint/13943/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-84987816114&partnerID=40&md5=e1d4439870306665643c6b31f372cbab

Phishing is an Internet fraud to entice unsuspecting victims. The tactic of phishing is to impersonate the trusted entities by employing both social engineering and technical subterfuge. Moreover, phishing is a form of online identity theft that creates a fake copy of popular site. There are many types of anti-phishing techniques available. However, they are mostly still in the infancy stage which may give false alarm to the user. Therefore, this research aims to develop a feature-based phishing detection technique to overcome the limitation. The proposed method involves aggregating new features with several existing features to form a sensitive features set. Based on the features set, the proposed method will utilise support vector machine to perform the classification. The experimental results show convincing performance with 95.33 percent of accuracy.