Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Improved Method Text Feature Extraction for Detection of Phishing Website

Author : Ganesh S.Gangthade 1 Shyam R. Gote 2 Sachin P. Khengte 3

Date of Publication :18th April 2017

Abstract: Phishing is a technique of gaining personal information of users from various web-sites. Sometimes it redirects the user to phish webpage to gain information of user like username, password, account and credit card details etc. Our main ambition here is to design system to provide safeguard to users against phishing attacks. Our work is mainly focuses on use of terms and URLs from web page to detect possible phishing patterns from web pages of phishing websites. Process initiates with pars-ing of web page to extract plain text terms and URLs. Further detected terms are fed to TF-IDF and URL weighting system to identify importance of each detected term. Later search engine lookup is carried out for most important terms which help to detect possible victim URLs for given input website. Finally WHOIS lookup is used to compare registration details of websites to correctly categorize website as phishing or legitimate one

Reference :

    1. Choon Lin Tan, Kang Leng Chiewy, San Nah Sze, “Phishing Website Detection Using URL-Assisted Brand Name Weighting System”, In IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), Pages 54-59, 2014
    2. (2014, June) Phishing guide part 1. PayPal Inc. [Online].Available:http://https:// www.paypal.com/ au/ webapps/mpp/security/generalunderstandphishing
    3. (2014, June) Phishing activity trends report, 2nd half / 2010.Anti-Phishing Working Group. [Online].Available:http://docs.apwg.org/reports/ apwg report h2 2010.pdf
    4. Y. Zhang, J. I. Hong, and L. F. Cranor, “Cantina: A content-based approach to detecting phishing web sites,” in Proceedings of the 16th International Conference on World Wide Web, ser. WWW ’07.New York,NY,US: ACM, 2007, pp. 639–648. [Online]. Available: http://doi.acm.org/ 10.1145/1242572.1242659

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