Phish Catcher: Client side defense against web spoofing attacks using machine learning

Authors

  • Dr. D.Madhavi, G. Sreeja, T. Chaitramaye, V. Manasa

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Abstract

Cybersecurity faces a huge issue in protecting users' personal information, including passwords and PIN codes, from unauthorised access. False login pages seeking sensitive information reach billions of visitors every day. A user may be tricked into visiting a malicious website by several means, including phishing emails, enticing adverts, click jacking, malware, SQL injection, session hijacking, man-in-the-middle attacks, denial of service, and cross-site scripting.

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References

W. Khan, A. Ahmad, A. Qamar, M. Kamran, and M. Altaf, ‘‘spoof Catch: A client-side protection tool against phishing attacks,’’ IT Prof., vol. 23, no. 2, pp. 65–74, Mar. 2021.

B. Schneier, ‘‘Two-factor authentication: Too little, too late,’’ Commun. ACM, vol. 48, no. 4, p. 136, Apr. 2005.

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Published

2024-12-02

How to Cite

Dr. D.Madhavi, G. Sreeja, T. Chaitramaye, V. Manasa. (2024). Phish Catcher: Client side defense against web spoofing attacks using machine learning . Pegem Journal of Education and Instruction, 13(4), 437–446. Retrieved from https://pegegog.net/index.php/pegegog/article/view/4005

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