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Phishing Website Detection Based on Effective CSS Features of Web Pages

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Wireless Algorithms, Systems, and Applications (WASA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10251))

Abstract

In a web-based phishing attack, an attacker sets up scam web pages to deceive users to input their sensitive information. The appearance of web pages plays an important role in deceiving users, and thus is a critical metric for detecting phishing web sites. In this paper, we propose a robust phishing page detection mechanism based on web pages’ visual similarity. To measure the similarity of the suspicious pages and victim pages accurately, we extract features from the Cascading Style Sheet (CSS) of web pages, and select the effective feature sets for similarity rating. We prototyped our approach in the Google Chrome browser and used it to analyze suspicious web pages. The proof of concept implementation verifies the effectiveness of our algorithm with a low performance overhead.

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Acknowledgment

This work was supported in part by the National Natural Science Foundation of China (No. 61402029), the National Natural Science Foundation of China (No. 61370190 and No. 61379002), Singapore Ministry of Education under NUS grant R-252-000-539-112.

Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, Beihang University, Beijing, China

    Jian Mao, Wenqian Tian & Pei Li

  2. School of Computing, National University of Singapore, Singapore, Singapore

    Zhenkai Liang

  3. Baidu USA LLC, Sunnyvale, CA, USA

    Tao Wei

Authors
  1. Jian Mao
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  2. Wenqian Tian
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  3. Pei Li
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  4. Tao Wei
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  5. Zhenkai Liang
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Corresponding author

Correspondence to Jian Mao .

Editor information

Editors and Affiliations

  1. Texas Christian University, Fort Worth, Texas, USA

    Liran Ma

  2. New Jersey Institute of Technology, Newark, New Jersey, USA

    Abdallah Khreishah

  3. University of Oslo, Oslo, Norway

    Yan Zhang

  4. University of North Georgia, Dahlonega, Georgia, USA

    Mingyuan Yan

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Mao, J., Tian, W., Li, P., Wei, T., Liang, Z. (2017). Phishing Website Detection Based on Effective CSS Features of Web Pages. In: Ma, L., Khreishah, A., Zhang, Y., Yan, M. (eds) Wireless Algorithms, Systems, and Applications. WASA 2017. Lecture Notes in Computer Science(), vol 10251. Springer, Cham. https://doi.org/10.1007/978-3-319-60033-8_68

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  • DOI: https://doi.org/10.1007/978-3-319-60033-8_68

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60032-1

  • Online ISBN: 978-3-319-60033-8

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