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Showing 1 to 4 of 4 for “"Statistical anomaly detection"”.

  1. Machine Learning–Based Detection of Network Failures in Core Network Cellular Data

    … traffic volumes, as well as the ap-plication of statistical anomaly detection techniques to remove abnormal traffic fluctuations. Both offline and online learning approaches are investigated for network traffic volume prediction and network failure classification. These predictive modelling are …

    stellenbosch Repository record for Machine Learning–Based Detection of Network Failures in Core Network Cellular Data (opens in a new tab)

  2. Real-time Intrusion Detection using Multidimensional Sequence-to-Sequence Machine Learning and Adaptive Stream Processing

    … There are host-based and network-based Intrusion Detection Systems (IDS's), of which there are each signature-based and anomaly-based detection methods. An anomalous network behavior can be defined as an intentional violation of the expected sequence of packets. In a real-time network-based IDS, …

    uwo Repository record for Real-time Intrusion Detection using Multidimensional Sequence-to-Sequence Machine Learning and Adaptive Stream Processing (opens in a new tab)

  3. Logic-Targeted Data Poisoning and Cascading Failures in AI-Driven Distributed Traffic Control Systems

    … single-point hardware failure. Standard anomaly detection methods were not effective because a zero-vehicle reading is physically plausible. The standard detector achieved an AUC close to 0.57, only slightly above random discrimination. This thesis proposes the False Vacuum Indicator …

    houston Repository record for Logic-Targeted Data Poisoning and Cascading Failures in AI-Driven Distributed Traffic Control Systems (opens in a new tab)