Towards detection of phishing websites on client-side using machine learning based approach

Author:

Jain Ankit Kumar,Gupta B. B.

Funder

Ministry of Electronics & Information Technology (MeitY), Government of India

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering

Reference35 articles.

1. Jain, A. K., & Gupta, B. B. (2017). Detection of phishing attacks in financial and e-banking websites using link and visual similarity relation. International Journal of Information and Computer Security, Inderscience, 2017 (Forthcoming Articles).

2. Gupta, S., & Gupta, B. B. (2017). Detection, avoidance, and attack pattern mechanisms in modern web application vulnerabilities: Present and future challenges. International Journal of Cloud Applications and Computing, 7(3), 1–43.

3. Almomani, A., et al. (2013). A survey of phishing email filtering techniques. IEEE Communications Surveys & Tutorials, 15.4, 2070–2090.

4. Gupta, B. B., et al. (2017). Fighting against phishing attacks: State of the art and future challenges. Neural Computing and Applications, 28(12), 3629–3654.

5. APWG Q4 2016 Report available at: http://docs.apwg.org/reports/apwg_trends_report_q4_2016.pdf . Last accessed on September 22, 2017.

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