ISSN2320-2882
Impact Factor9.17
UGC ParametersAligned
Low Cost₹1501 / $59
CrossRefDOI
ESTD2013
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Phishing Website Detection System based on Machine Learning
Authors
Suresh V Reddy , Harshali Bodkhe , Sreekrishna Bigala , Uzair Siddiqui , Hariom Kalyani,Ajay Kakade
Keywords
Phishing Detection, Machine Learning, Website Security, Online Fraud Prevention
Abstract
Phishing websites have become one of the most common ways attackers trick people into sharing sensitive details like passwords and banking information. Since new fake websites are created every day, traditional methods such as blacklists are not always effective. In this paper, we present PhishGuard, a system designed to detect phishing websites using machine learning. The system extracts features from website URLs, page content, and SSL certificates, and then applies classification algorithms to predict whether the site is genuine or fake. Our experiments show that Random Forest performed better than other models, achieving about 96% accuracy. With this approach, PhishGuard provides an additional layer of online security and helps reduce the risk of phishing attacks.
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IJCRT — journal style
"Phishing Website Detection System based on Machine Learning", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.13, Issue 10, page no.87-90, October 2025, Available :https://ijcrt.org/papers/IJCRTBH02019.pdf
APA — 7th edition
Reddy, S. V., Bodkhe, H., Bigala, S., Siddiqui, U., & Hariom Kalyani, A. K. (2025). Phishing Website Detection System based on Machine Learning. International Journal of Creative Research Thoughts, 13(10), 87-90. https://ijcrt.org/viewpaperforall.php?paper=IJCRTBH02019
MLA — 9th edition
Reddy, Suresh V, et al. "Phishing Website Detection System based on Machine Learning." International Journal of Creative Research Thoughts, vol. 13, no. 10, 2025, pp. 87-90, https://ijcrt.org/viewpaperforall.php?paper=IJCRTBH02019.
Chicago — 17th, bibliography
Reddy, Suresh V, et al. "Phishing Website Detection System based on Machine Learning." International Journal of Creative Research Thoughts 13, no. 10 (2025): 87-90. https://ijcrt.org/viewpaperforall.php?paper=IJCRTBH02019.
Harvard — author–date
Reddy, S.V. et al. (2025) 'Phishing Website Detection System based on Machine Learning', International Journal of Creative Research Thoughts, 13(10), pp. 87-90. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRTBH02019
IEEE — numbered reference
S. V. Reddy, H. Bodkhe, S. Bigala, U. Siddiqui and A. K. Hariom Kalyani, "Phishing Website Detection System based on Machine Learning," IJCRT, vol. 13, no. 10, pp. 87-90, Oct. 2025.
Vancouver — biomedical
Reddy SV, Bodkhe H, Bigala S, Siddiqui U, Hariom Kalyani AK. Phishing Website Detection System based on Machine Learning. IJCRT. 2025 Oct;13(10):87-90.
AMA — 11th edition
Reddy SV, Bodkhe H, Bigala S, Siddiqui U, Hariom Kalyani AK. Phishing Website Detection System based on Machine Learning. IJCRT. 2025;13(10):87-90. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRTBH02019
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRTBH02019,
author = {Suresh V Reddy and Harshali Bodkhe and Sreekrishna Bigala and Uzair Siddiqui and Ajay Kakade Hariom Kalyani},
title = {Phishing Website Detection System based on Machine Learning},
journal = {International Journal of Creative Research Thoughts},
volume = {13},
number = {10},
pages = {87-90},
year = {2025},
month = {October},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRTBH02019}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Reddy, Suresh V
AU - Bodkhe, Harshali
AU - Bigala, Sreekrishna
AU - Siddiqui, Uzair
AU - Hariom Kalyani, Ajay Kakade
TI - Phishing Website Detection System based on Machine Learning
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 13
IS - 10
PY - 2025
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRTBH02019
SP - 87
EP - 90
ER -
Issue
Volume 13 Issue 10,
October-2025
Pages : 87-90
Article Information
- Published In
- International Journal of Creative Research Thoughts — Volume 13, Issue 10, October 2025
- Pages
- 87-90
- Published
- October 2025
- Registration ID
- IJCRT_295195
- Published Paper ID
- IJCRTBH02019
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 284
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRTBH02019
- Published Paper PDF
- https://ijcrt.org/papers/IJCRTBH02019.pdf
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International Journal of Creative Research Thoughts
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2320-2882
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The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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