Detecting visually similar Web pages

Author:

Chen Teh-Chung1,Dick Scott1,Miller James1

Affiliation:

1. University of Alberta, Canada

Abstract

We propose a novel approach for detecting visual similarity between two Web pages. The proposed approach applies Gestalt theory and considers a Web page as a single indivisible entity. The concept of supersignals, as a realization of Gestalt principles, supports our contention that Web pages must be treated as indivisible entities. We objectify, and directly compare, these indivisible supersignals using algorithmic complexity theory. We illustrate our approach by applying it to the problem of detecting phishing scams. Via a large-scale, real-world case study, we demonstrate that 1) our approach effectively detects similar Web pages; and 2) it accuractely distinguishes legitimate and phishing pages.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference82 articles.

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