Visual Similarity-Based Phishing Detection Scheme Using Image and CSS with Target Website Finder

Shuichiro Haruta, Hiromu Asahina, Iwao Sasase

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The detection of phishing websites and identifying their target are imperative. Among several phishing detection schemes, the scheme using visual similarity is gathering attention. It takes a screenshot of website and stores it to the database. If the inputted website''s screenshot is similar to database''s one, it is judged as phishing. However, if multiple similar websites exist, the first inputted website is regarded as legitimate. As a result, it cannot correctly detect legitimate website and identifying phishing target becomes difficult. As a second shortcoming, if the screenshot of phishing website is locally different from ones in the database, false negative occurs. In this paper, we propose visual similarity-based phishing detection scheme using image and CSS with target website finder. To remedy first shortcoming, we focus on the fact that legitimate websites are often linked by other websites and regard such website as legitimate and store the screenshot and CSS in the database. Since CSS is a file which defines the websites visual contents, attackers often steal legitimate CSS to mimic the legitimate website. Thus, by detecting the website which plagiarizes appearance or CSS of legitimate website, we detect phishing website and its target simultaneously. Moreover, we can alleviate the second shortcoming by using CSS because it is probable that the websites which have locally different appearance use identical CSS. By computer simulation with real dataset, we demonstrate our scheme improves detection accuracy while finding phishing target.

Original languageEnglish
Title of host publication2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
Volume2018-January
ISBN (Electronic)9781509050192
DOIs
Publication statusPublished - 2018 Jan 10
Event2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore
Duration: 2017 Dec 42017 Dec 8

Other

Other2017 IEEE Global Communications Conference, GLOBECOM 2017
CountrySingapore
CitySingapore
Period17/12/417/12/8

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

Cite this

Haruta, S., Asahina, H., & Sasase, I. (2018). Visual Similarity-Based Phishing Detection Scheme Using Image and CSS with Target Website Finder. In 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings (Vol. 2018-January, pp. 1-6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2017.8254506