| Autor: |
Machap, Kamalakannan, Murakami, Rin, Rahman, Nor Azlina Abdul |
| Předmět: |
|
| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3161 Issue 1, p1-6, 6p |
| Abstrakt: |
This paper is focusing on the development of a efficient Chrome extension designed to detect phishing websites. Phishing attacks continue to pose a significant threat to online users, compromising their sensitive information and causing financial losses. The proposed extension utilizes random forest machine learning algorithm to analyze website URL, enabling the identification and alerting of potential phishing attempts. By integrating with the user's browsing experience, the extension provides a proactive defense mechanism, empowering users to make informed decisions and stay protected from phishing attacks. The research work effectiveness is evaluated through extensive testing. Overall, this research contributes to enhancing user security and privacy in the online ecosystem, with implications for both individual users and organizations concerned with cybersecurity. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
