Data-driven Anomaly Detection with Timing Features for Embedded Systems.
Sixing LuRoman LyseckyPublished in: ACM Trans. Design Autom. Electr. Syst. (2019)
Keyphrases
- anomaly detection
- embedded systems
- data driven
- intrusion detection
- detecting anomalies
- network intrusion detection
- low cost
- embedded devices
- feature extraction
- unsupervised learning
- intrusion detection system
- detecting anomalous
- network security
- network traffic
- embedded software
- anomalous behavior
- feature vectors
- computing power
- negative selection algorithm
- malware detection
- resource limited
- network anomaly detection
- unsupervised anomaly detection
- open source
- network intrusion
- detect anomalies
- feature selection
- training data
- reinforcement learning
- feature space
- pairwise