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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM13584

Detecting Phishing Website Using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM13584

Volume:

6 |

5 |

May 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM13584

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

JK

Jay Kaphale

PK

Pratik Kamble

DB

Dinesh Borole

OC

Omkar Chavan

PRD

Prof. Ruchira Deshmukh

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Abstract

Phishing attack is a simplest way to obtain sensitive information from innocent users. Aim of the phishers is to acquire critical information like username, password and bank account details. Cyber security persons are now looking for trustworthy and steady detection techniques for phishing websites detection. This paper deals with machine learning technology for detection of phishing URLs by extracting and analyzing various features of legitimate and phishing URLs. Decision Tree, random forest and Support vector machine algorithms are used to detect phishing websites. Aim of the paper is to detect phishing URLs as well as narrow down to best machine learning algorithm by comparing accuracy rate, false positive and false negative rate of each algorithm.

KEYWORDS

Phishing attack Machine learning

Cite This Article

Jay Kaphale, Pratik Kamble, Dinesh Borole, Omkar Chavan, Prof. Ruchira Deshmukh, "Detecting Phishing Website Using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 5, May 2022. https://doi.org/10.55041/IJSREM13584

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Publication Date

6/11/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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