Web Traffic Anomaly Detection Using Isolation Forest

Web Traffic Anomaly Detection Using Isolation Forest

As companies increasingly undergo digital transformation, the value of their data assets also rises, making them even more attractive targets for hackers. The large volume of weblogs warrants the use of advanced classification methodologies in order for cybersecurity specialists to identify web traf...

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Bibliographic Details
Main Authors: Wilson Chua, Arsenn Lorette Diamond Pajas, Crizelle Shane Castro, Sean Patrick Panganiban, April Joy Pasuquin, Merwin Jan Purganan, Rica Malupeng, Divine Jessa Pingad, John Paul Orolfo, Haron Hakeen Lua, Lemuel Clark Velasco
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Informatics
Subjects:
anomaly detection
web traffic
web traffic anomaly detection
machine learning
isolation forest
Online Access:https://www.mdpi.com/2227-9709/11/4/83
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