Paper Title

Phishing Website Detection Using Machine Learning

Article Identifiers

Registration ID: IJNRD_189732

Published ID: IJNRD2303403

DOI: Click Here to Get

Authors

Fouziya Farheen , Balineni Ram Deepak , Nirupam Kumar Sasapu , Sagar Chanchlani

Keywords

Phishing, Phishing website detection, Machine Learning, KNN, SVM, Random Forest

Abstract

The Internet's advancement has drawn attention to network security, as a secure network environment is fundamental for the Internet's fast and healthy growth. Cybercriminals employ phishing, a malicious act of deceiving users into clicking on phishing links, stealing their information, and using it to fake logins and steal funds. Network security is an iterative issue of attack and defense, and phishing and its detection technology continually evolve. Blacklists and whitelists are traditional methods for identifying phishing links but fail to identify new ones, which necessitates predicting whether a new link is a phishing website and improving the prediction's accuracy. Machine learning has emerged as a critical tool in predicting phishing websites, with this paper offering system learning technology for the detection of phishing URLs via extracting and studying diverse functions of valid and phishing URLs. KNN Classifier, Random Forest, and Support Vector Machine algorithms are used to locate phishing websites. The paper aims to detect phishing URLs as well as narrow them down to the fine algorithm that gets to know the set of rules with the aid of using evaluating the accuracy rate.

How To Cite (APA)

Fouziya Farheen, Balineni Ram Deepak, Nirupam Kumar Sasapu, & Sagar Chanchlani (March-2023). Phishing Website Detection Using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(3), e13-e20. https://ijnrd.org/papers/IJNRD2303403.pdf

Issue

Volume 8 Issue 3, March-2023

Pages : e13-e20

Other Publication Details

Paper Reg. ID: IJNRD_189732

Published Paper Id: IJNRD2303403

Downloads: 000121980

Research Area: Engineering

Country: Visakhapatnam, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303403.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303403

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

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Subject Category: Research Area

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