Machine Learning for the Detection of Uniform Resource Locator Phishing

Author:

S. Muthuselvan1ORCID,R. Karthikeyan2,M. Rajasekaran3,K. Rajakumari4,S. Rajes kannan5,S. Anupriya6

Affiliation:

1. KCG College of Technology, India

2. Aarupadai Veedu Institute of Technology, India

3. Madanapalle Institute of Technology and Science, India

4. Bharath Institute of Higher Education and Research, India

5. Chennai Institute of Technology, India

6. Vels Institute of Science, Technology, and Advanced Studies, India

Abstract

In recent times, phishing attempts have grown in frequency as fraudsters employ diverse tactics to deceive gullible victims into divulging confidential information, like financial details or login credentials. One of the most common methods of phishing is through the use of URLs, where attackers create fake web pages that mimic legitimate sites and use them to steal information from users to combat this threat, researchers and security experts have turned to machine learning techniques to develop algorithms that can accurately detect phishing URLs. In this paper,review the current state of the art in URL phishing detection using machine learning, including the various approaches and algorithms that have been developed.

Publisher

IGI Global

Reference21 articles.

1. Phishing detection using machine learning classifiers;G.Ahmed;Journal of Information Security and Applications,2020

2. Detecting phishing websites using machine learning algorithms;H. A. M.Al-Quraishi;International Journal of Computer Science and Information Security,2018

3. Phishing websites detection using machine learning algorithms;A. S.AlHajri;2020 International Conference on Advanced Machine Learning Technologies and Applications (AMLTA)

4. Alqahtani, S. F., & Rafique, D. D. (2017). Detection of phishing URLs using machine learning techniques. 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), 142-147.

5. IoT Framework for Measurement and Precision Agriculture: Predicting the Crop Using Machine Learning Algorithms

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3