SigML++: Supervised Log Anomaly with Probabilistic Polynomial Approximation

SigML++: Supervised Log Anomaly with Probabilistic Polynomial Approximation

Security log collection and storage are essential for organizations worldwide. Log analysis can help recognize probable security breaches and is often required by law. However, many organizations commission log management to Cloud Service Providers (CSPs), where the logs are collected, processed, an...

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Bibliographic Details
Main Authors: Devharsh Trivedi, Aymen Boudguiga, Nesrine Kaaniche, Nikos Triandopoulos
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Cryptography
Subjects:
sigmoid function approximation
private machine learning
fully homomorphic encryption
log anomaly detection
supervised machine learning
probabilistic polynomial approximation
Online Access:https://www.mdpi.com/2410-387X/7/4/52

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https://www.mdpi.com/2410-387X/7/4/52

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