A mobile sensing method to counteract social media website impersonation. (October 2016)

• Record Type: Journal Article
• Authors: ELMassry, Mohamed Y; AlMogren, Ahmad S
• Is Part Of: International journal of distributed sensor networks. Volume 12:Number 10(2016)
• Publication Date: 2016-10
• Subjects: Phishing detection -- website impersonation -- pixel-by-pixel blacklist -- whitelist -- extensible markup language phishing -- mobile sensing -- visual similarity; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147716671265
• Languages: English
• ISSNs: 1550-1329

Abstract

Phishing is a serious threat to online users, especially since attackers have tremendously improved their techniques in impersonating important websites. With websites looking visually the same, users are fooled more easily. Visual similarity algorithms may help to detect and counteract some phished websites. Through similarity algorithms, the phishers play with the colors and visual properties of the website in a way that cannot be noticed by the users. However, the phishers make the unnoticed changes to fool the similarity algorithms as well. In this article, we propose an efficient phishing website detection algorithm using three-step checking. The performance results are compared to the state-of-the-art approaches that show new kinds of phishing warnings with better outcomes and less false positives. Our approach provides similar accuracy to the blacklisting methods with the advantage that it can easily classify the phishing websites with less overhead and without being victimized.