| Probabilistic Anomaly Detection in Distributed Computer (2006) | |||||||||||||||||
Abstract | |||||||||||||||||
| A form of distributed, lazy evaluation is presented for anomaly detection in computers. Using a two dimensional time parameterization, and a geometric Markovian memory, we discuss a three tiered probabilistic method of classifying anomalous behaviour in periodic time. This leads to a computationally cheap means of finding probable faults amongst the symptoms of network and system behaviour. Keywords: Machine learning, anomaly detection 1. | |||||||||||||||||
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