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A Phishing Webpage Detecting Algorithm Using Webpage Noise and N-Gram

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Book cover Cloud Computing and Security (ICCCS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10039))

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Abstract

Although anti-phishing solutions were highly publicized, phishing attack has been still an important serious problem. In this paper, a novel phishing webpage detecting algorithm using the webpage noise and n-gram was proposed. Firstly, the phishing webpage detecting algorithm extracts the webpage noise from suspicious websites, and then expresses it as a feature vector by using n-gram. Lastly, the similarity of feature vector between the protected website and suspicious is calculated. Experimental results on detecting phishing sites samples data show that: this algorithm is more effective, accurate and quick than existing algorithms to detect whether a site is a phishing website.

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Acknowledgment

This study is supported by National Natural Science Foundation of China (No. 61304208), Hunan Province Natural Science Foundation of China (No. 13JJ2031); Youth Scientific Research Foundation of Central South University of Forestry & Technology (No. QJ2012009A).

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Authors and Affiliations

  1. College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha, 410004, China

    Qiong Deng, Huajun Huang, Liangmin Pan, Shuang Pang & Jiaohua Qin

Authors
  1. Qiong Deng
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  2. Huajun Huang
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  3. Liangmin Pan
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  4. Shuang Pang
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  5. Jiaohua Qin
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Corresponding author

Correspondence to Huajun Huang .

Editor information

Editors and Affiliations

  1. University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Michigan State University , EAST LANSING, Michigan, USA

    Alex Liu

  3. National Dong Hwa University , Shoufeng, Taiwan

    Han-Chieh Chao

  4. Purdue University , West Lafayette, Indiana, USA

    Elisa Bertino

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Deng, Q., Huang, H., Pan, L., Pang, S., Qin, J. (2016). A Phishing Webpage Detecting Algorithm Using Webpage Noise and N-Gram. In: Sun, X., Liu, A., Chao, HC., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2016. Lecture Notes in Computer Science(), vol 10039. Springer, Cham. https://doi.org/10.1007/978-3-319-48671-0_15

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  • DOI: https://doi.org/10.1007/978-3-319-48671-0_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48670-3

  • Online ISBN: 978-3-319-48671-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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