Self-Supervised Anomaly Detection from Anomalous Training Data via Iterative Latent Token Masking.
Ashay PatelPetru-Daniel TudosiuWalter H. L. PinayaMark S. GrahamOlusola AdelekeGary J. CookVicky GohSébastien OurselinM. Jorge CardosoPublished in: ICCV (Workshops) (2023)
Keyphrases
- anomaly detection
- training data
- intrusion detection
- anomalous behavior
- network intrusion detection
- detecting anomalies
- detecting anomalous
- learning algorithm
- computer security
- network traffic
- decision trees
- training set
- unsupervised anomaly detection
- supervised learning
- latent variables
- detect anomalies
- network anomaly detection
- one class support vector machines
- data sets
- intrusion detection system
- behavior analysis
- neural network
- unsupervised learning
- network security
- data warehouse
- object recognition
- pattern recognition
- negative selection algorithm
- connectionist systems