Litcius/Paper detail

usfAD: a robust anomaly detector based on unsupervised stochastic forest

Sunil Aryal, KC Santosh, Richard Dazeley

2020International Journal of Machine Learning and Cybernetics19 citationsDOIOpen Access PDF

Topics & Concepts

Anomaly detectionComputer scienceOutlierHistogramData miningPattern recognition (psychology)Anomaly (physics)Probabilistic logicLocal outlier factorArtificial intelligenceIntrusion detection systemSupport vector machineDetectorRandom forestImage (mathematics)TelecommunicationsPhysicsCondensed matter physicsNetwork Security and Intrusion DetectionAnomaly Detection Techniques and ApplicationsAdvanced Malware Detection Techniques
usfAD: a robust anomaly detector based on unsupervised stochastic forest | Litcius