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Unsupervised Anomaly Detection in Network Intrusion Detection Using Clusters.

, and . ACSC, volume 38 of CRPIT, page 333-342. Australian Computer Society, (2005)

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A scalable sampling scheme for clustering in network traffic analysis., , and . Infoscale, volume 304 of ACM International Conference Proceeding Series, page 38. ACM, (2007)Characteristic-Based Descriptors for Motion Sequence Recognition., , , and . PAKDD, volume 5012 of Lecture Notes in Computer Science, page 369-380. Springer, (2008)Robust and Accurate Short-Term Load Forecasting: A Cluster Oriented Ensemble Learning Approach., , and . IJCNN, page 1-8. IEEE, (2019)Parking availability prediction for sensor-enabled car parks in smart cities., , and . ISSNIP, page 1-6. IEEE, (2015)CESVM: Centered Hyperellipsoidal Support Vector Machine Based Anomaly Detection., , and . ICC, page 1610-1614. IEEE, (2008)Privacy-Preserving Collaborative Anomaly Detection for Participatory Sensing., , , , and . PAKDD (1), volume 8443 of Lecture Notes in Computer Science, page 581-593. Springer, (2014)Improving load forecasting based on deep learning and K-shape clustering., , , , and . IJCNN, page 4134-4141. IEEE, (2017)Fuzzy c-Shape: A new algorithm for clustering finite time series waveforms., , , , and . FUZZ-IEEE, page 1-8. IEEE, (2017)Extension of iVAT to asymmetric matrices., , , and . FUZZ-IEEE, IEEE, (2013)Pattern based anomalous user detection in cognitive radio networks., , and . ICASSP, page 5605-5609. IEEE, (2015)