Using visual website similarity for phishing detection and reporting

Abstract

Phishing is a severe threat to online users, especially since attackers improve in impersonating other websites [1]. With websites looking visually the same, users are fooled more easily (see figure 1). However, the close visual similarity can also be used to counteract phishing. We present a framework that uses visual website similarity: (1) to detect possible phishing websites and (2) to create better warnings for such attacks. We report first results together with the three step process planned for the project. We expect the detection results to be comparable to previously published work which would allow for new kinds of phishing warnings with better coverage, less false positives and explicit user recommendations how to avoid these critical situation.

User experiences of TORPEDO: TOoltip-poweRed Phishing Email DetectiOn

“…Web browsers or AddOns can check the URL against various blacklists or check the web site content in combination with the actual URL. A number of different approaches for these checks have been proposed [28,4,29,32]. In both pre-and post-click checks a risky situation can either lead to blocking or a warning e.g., [25,30,45,43].…”

TORPEDO: TOoltip-poweRed Phishing Email DetectiOn

“…Web browsers or Add-ons can check the URL against various blacklists or check the web site content in combination with the actual URL. A number of different approaches for these checks have been proposed [27,3,28,31]. In both pre-and post-click checks a risky situation can either lead to blocking or a warning e.g.…”

A Computer Vision Technique to Detect Phishing Attacks

“…Maurer and Herzner [15] detects phishing based on the comparisons of color and texture histograms of both suspicious and target site. Wu et al [16] divide the webpage into "blocks" based on its layout and identifier features from the blocks.…”