A phishing webpage detecting algorithm using webpage noise and N-Gram

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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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Deng, Q., Huang, H., Pan, L., Pang, S., & Qin, J. (2016). A phishing webpage detecting algorithm using webpage noise and N-Gram. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10039 LNCS, pp. 156–165). Springer Verlag. https://doi.org/10.1007/978-3-319-48671-0_15

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