Phish-Sight: a new approach for phishing detection using dominant colors on web pages and machine learning

Author:

Pandey PankajORCID,Mishra NishcholORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality,Information Systems,Software

Reference63 articles.

1. Jain, A.K., Gupta, B.B.: Detection of phishing attacks in financial and e-banking websites using link and visual similarity relation. Int. J. Inf. Comput. Secur. 10(4), 398–417 (2018)

2. Akiyama, M., Yagi, T., Hariu, T., Kadobayashi, Y.: Honeycirculator: distributing credential honeytoken for introspection of web-based attack cycle. Int. J. Inf. Secur. 17(2), 135–151 (2018)

3. Gupta, S., Gupta, B.B.: Detection, avoidance, and attack pattern mechanisms in modern web application vulnerabilities: present and future challenges. Int. J. Cloud Appl. Comput. (IJCAC) 7(3), 1–43 (2017)

4. Almomani, A., Gupta, B.B., Atawneh, S., Meulenberg, A., Almomani, E.: A survey of phishing email filtering techniques. IEEE Commun. Surv. Tutor. 15(4), 2070–2090 (2013)

5. APWG.: APWG trends report q3,2021 (2021). https://docs.apwg.org/reports/apwg_trends_report_q3_2021.PDF. Accessed 15 Oct 2021

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