Lightweight Long Short-Term Memory Variational Auto-Encoder for Multivariate Time Series Anomaly Detection in Industrial Control Systems

Lightweight Long Short-Term Memory Variational Auto-Encoder for Multivariate Time Series Anomaly Detection in Industrial Control Systems

Heterogeneous cyberattacks against industrial control systems (ICSs) have had a strong impact on the physical world in recent decades. Connecting devices to the internet enables new attack surfaces for attackers. The intrusion of ICSs, such as the manipulation of industrial sensory or actuator data,...

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Bibliographic Details
Main Authors: Damer, N. (Author), Fährmann, D. (Author), Kirchbuchner, F. (Author), Kuijper, A. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
anomaly detection
Anomaly detection
Auto encoders
Brain
Cyber security
Cyber-attacks
Encoder architecture
Industrial control systems
Long short-term memory
Multivariate time series
pattern recognition
Pattern recognition
Physical world
security
Security
System behaviors
Water supply systems
Water treatment
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Internet

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