Design and Evaluation of Unsupervised Machine Learning Models for Anomaly Detection in Streaming Cybersecurity Logs

Design and Evaluation of Unsupervised Machine Learning Models for Anomaly Detection in Streaming Cybersecurity Logs

Companies, institutions or governments process large amounts of data for the development of their activities. This knowledge usually comes from devices that collect data from various sources. Processing them in real time is essential to ensure the flow of information about the current state of infra...

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Bibliographic Details
Main Authors: Carmen Sánchez-Zas, Xavier Larriva-Novo, Víctor A. Villagrá, Mario Sanz Rodrigo, José Ignacio Moreno
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Mathematics
Subjects:
machine learning
clustering
real-time
data pre-processing
threshold
Spark
Online Access:https://www.mdpi.com/2227-7390/10/21/4043

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