| F. Zhang and J. L. Hellerstein. An approach to on-line predictive detection. In Proceedings of MASCOTS 2000, August 2000. |
....between normal operation and attack, should be declared Key Variables at the Target. Since we are looking to localized variations in the variables, the time series should be segmented on small sub time series, which are then compared with normal profiles. This procedure was used in [15] and [16] for detecting anomalies in network operation, due to component faults. Anomalies were detected as variations on the parameters of AutoRegressive models. For the case of Denial of Service attacks however, the traffic variations in the Target are so intense, that much simpler procedures can be em7 ....
F. Zhang and J. Hellerstein. An Approach to On-Line Predictive Detection. In Proceedings of the Eighth International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, pages 549--556, San Francisco, CA, August 2000. IEEE Computer Society. 14
No context found.
F. Zhang and J. L. Hellerstein. An approach to on-line predictive detection. In Proceedings of MASCOTS 2000, August 2000.
No context found.
F. Zhang and J. L. Hellerstein. An approach to on-line predictive detection. In Proceedings of MASCOTS 2000.
No context found.
F. Zhang and J. L. Hellerstein. An approach to on-line predictive detection. In Proceedings of MASCOTS 2000.
No context found.
F. Zhang and J. L. Hellerstein. An approach to on-line predictive detection. In Proceedings of MASCOTS 2000.
No context found.
F. Zhang and J. L. Hellerstein. An approach to on-line predictive detection. In Proceedings of MASCOTS 2000, August 2000.
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