Malware and Phishing URL Detection using Machine Learning
Zenodo, 2023
Online
unknown
Zugriff:
Phishing URLs and malicious software pose a serious risk to both individuals and organizations. These assaults may lead to financial loss, reputational harm, and data breaches. Security experts have created several tools and methods to identify and stop the propagation of malware and phishing URLs to tackle these threats. Using machine learning algorithms to identify malware and phishing URLs is one of the most efficient ways to do so. In order to find trends and traits linked to harmful websites and software, these algorithms analyze historical data. After being trained on this data, a model can then be used to scan emails and web pages for suspicious content.
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Malware and Phishing URL Detection using Machine Learning
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Autor/in / Beteiligte Person: | Shapna Rani, E ; Anushree, A ; Guhan, S ; Nancy Pricilla, R ; Aishvariya, B B |
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Veröffentlichung: | Zenodo, 2023 |
Medientyp: | unknown |
DOI: | 10.5281/zenodo.7942436 |
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