UGC Approved Journal no 63975(19)

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Published in:

Volume 10 Issue 11
November-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2311367


Registration ID:
528198

Page Number

d537-d540

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Title

INTELLIGENT METHODS FOR ACCURATELY DETECTING PHISHING WEBSITES

Abstract

Phishing attacks pose a severe threat to online security, making the accurate detection of phishing URLs a critical endeavor. This abstract introduces a novel approach that leverages intelligent methods based on machine learning algorithms to enhance the precision of phishing URL detection. In an era where cybercriminals continuously adapt and evolve their tactics, this research aims to develop a robust and proactive defense mechanism. By harnessing the power of machine learning, this study seeks to train models capable of identifying subtle patterns and characteristics in URLs that are indicative of phishing attempts. Through a comprehensive analysis of various features, including domain structure, textual content, and lexical attributes, the proposed methods aim to provide a multi-faceted and dynamic approach to detect phishing URLs, ultimately bolstering cybersecurity efforts. The proposed work focuses on the design and evaluation of a range of machine learning algorithms, including decision trees, random forests, and naive bays, to uncover the most effective techniques for phishing URL detection. By harnessing a diverse set of features and utilizing labeled datasets for training, the models are expected to learn and adapt to emerging phishing techniques. As phishing threats continue to evolve in complexity and scale, the integration of intelligent methods based on machine learning is poised to be a critical step forward in the ongoing battle to protect digital identities and sensitive information.

Key Words

Phishing URL Detection, Cybersecurity, Feature Analysis, Decision Trees, Random Forests, Pattern Recognition

Cite This Article

"INTELLIGENT METHODS FOR ACCURATELY DETECTING PHISHING WEBSITES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.d537-d540, November-2023, Available :http://www.jetir.org/papers/JETIR2311367.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"INTELLIGENT METHODS FOR ACCURATELY DETECTING PHISHING WEBSITES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppd537-d540, November-2023, Available at : http://www.jetir.org/papers/JETIR2311367.pdf

Publication Details

Published Paper ID: JETIR2311367
Registration ID: 528198
Published In: Volume 10 | Issue 11 | Year November-2023
DOI (Digital Object Identifier):
Page No: d537-d540
Country: Nashik, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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