UNMASKING CYBER THREATS - LEVERAGING MACHINE LEARNING TO DETECT PHISHING WEBSITES
DOI:
https://doi.org/10.48047/CU/54/04/488-502Keywords:
phishing, cyber-attacks, statistical, machine learning, surfing.Abstract
Nowadays, smart phones are widely used, which makes them sus- ceptible to phishing. The majority of phishing websites attempt to obtain the victim's data by using the same user interface and universal resource location (URL) as the legitimate websites (user name, password, credit card details, etc.). Protecting users from cyberattacks requires an intelligent strategy. Phish- ing can hurt a company in a number of ways, including loss of financial proper- ty, intellectual loss, reputation damage, and disturbance of business activities. As a result, there is a pressing need for a mobile phishing detection system
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References
Z. Fan, "Detecting and Classifying Phishing Websites by Machine Learning," 2021 3rd International Conference
on Applied Machine Learning (ICAML), 2021, pp. 48-51, doi: 10.1109/ICAML54311.2021.00018.
S. Singh, M. P. Singh and R. Pandey, "Phishing Detection from URLs Using Deep Learning Ap- proach," 2020 5th International Conference on Computing, Communication and Security (ICCCS), 2020, pp. 1-4, doi: 10.1109/ICCCS49678.2020.9277459.)
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