Review paper
Detecting Anomalous Behavior in Cloud Servers by Nested-Arc Hidden SEMI-Markov Model with State Summarization
Abstract
Anomaly detection for cloud servers is important for detecting zero-day attacks. However, it is very challenging due to the large amount of accumulated data. In this paper, a new mathematical model for modeling dynamic usage behavior and detecting anomalies is proposed. It is constructed using state summarization and a novel nested-arc hidden semi-Markov model (NAHSMM). State summarization is designed to extract usage behavior reflective states...
Paper Details
Title
Detecting Anomalous Behavior in Cloud Servers by Nested-Arc Hidden SEMI-Markov Model with State Summarization
Published Date
Sep 1, 2019
Volume
5
Issue
3
Pages
305 - 316
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