Author Login IJIRT Partner Network (IPN) Login

Phishing website detection through website traffic using Machine Learning

  • Unique Paper ID: 164321
  • Volume: 10
  • Issue: 12
  • PageNo: 1339-1334
  • Abstract:
  • Web sites traffic largely encourage the expansion of illegal activities on the Internet and restrict the growth of Web services. Consequently, there's been a great drive for the development of methodical approaches to discourage consumers visiting these kinds of websites. Our suggestion is to use a learning-based method to divide websites into two categories: high and low. Our approach does not access the content of the websites; it just analyzes the Uniform Resource Locator. Consequently, it removes the chance of exposing users to browser-based vulnerabilities and run-time latency. With the help of learning algorithms, our system performs better in terms of generality and coverage with the blacklist service. The website URLs are divided into two classes: High: Secure websites offering standard services Low: Websites try to overwhelm consumers via advertisements or other content, such deceptive surveys.
Download article email to a friend

Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 1339-1334

Phishing website detection through website traffic using Machine Learning

Related Articles

Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Archive

View More

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry