A Lightweight Anti-Phishing Technique for Mobile Phone

Abstract

Mobile phones have become an essential device for accessing the web. This is due to the advantages of portability, lower cost and ease. However, the adoption of mobile phones for online activities is now being challenged by myriads of cybercrimes. One of such crimes is phishing attack. In this work, a lightweight anti-phishing technique is proposed to combat phishing attacks on mobile devices. This is necessary because these mobile platforms have increased the attack surface for phishers while diminishing the effectiveness of existing countermeasures. The proposed approach uses a number of URL behavior to determine the status of a website based on frequency analysis of extracted phishing features from PhishTank. To increase the detection power of unknown pattern, a machine learning algorithm called Support Vector Machine is adopted. The results indicated that the approach is very efficient against phishing sites with negligible false negatives.

Efficient Detection of Phishing Websites Using Multilayer Perceptron

“…The main drawback of the blacklist model is the period of time needed to recognize the phishing sites; sometimes it takes zero-day (0_day) and sometimes takes months which is enough time to fraud for multiple victims. The second solution is heuristics-based solutions, where the heuristics algorithms study the URL features and predict if the URL is trusted or malicious [10].…”

Phishing Techniques in Mobile Devices

“…In [20], a light weight technique is used. It uses some URL features to determine legitimacy of a webpage based on frequency analysis of extracted features phishing URLs.…”