Phishing URL Detection using PSO Optimized Support Vector Machine

Journal

International Journal of Digital Applications and Contemporary Research (IJDACR)

ISSN

2319-4863

Volume / Issue

Vol.7 · Issue 9

Published

April 2019

Access

Open Access

Licence

CC BY-NC-SA 4.0

Ankit Shrivastava Dr. Sudhir Agrawal

This paper aims to collect, map and model elements that will lead to the finding of phishing URL automatically, for this purpose data mining is used as basic tools, in this sense, it is considered that the existing patterns in a URL make it possible to distinguish the legitimate link for pages, the identification of these patterns will serve to model a successful classification method, for this purpose, the attributes found in the database "phishing web" that correspond to patterns of phishing pages will be validated, at the same time will be evaluated algorithms extracted from the literature that allow a better classification of records, finally, a model with the highest precision results is delivered which consists of particle swarm optimized support vector machine classifier.

Benign Phish Phishing URL PSO SVM

Ankit Shrivastava, Dr. Sudhir Agrawal (2019). Phishing URL Detection using PSO Optimized Support Vector Machine. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.7, Issue 9. ISSN: 2319-4863.

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