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    Adaptive Kalman filtering for anomaly detection in software appliances.


    Knorn, Florian and Leith, Douglas J. (2008) Adaptive Kalman filtering for anomaly detection in software appliances. In: IEEE Conference on Computer Communications Workshops, 2008. IEEE. ISBN 978-1-4244-2219-7

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    Abstract

    Availability and reliability are often important features of key software appliances such as firewalls, web servers, etc. In this paper we seek to go beyond the simple heartbeat monitoring that is widely used for failover control. We do this by integrating more fine grained measurements that are readily available on most platforms to detect possible faults or the onset of failures. In particular, we evaluate the use of adaptive Kalman Filtering for automated CPU usage prediction that is then used to detect abnormal behaviour. Examples from experimental tests are given.

    Item Type: Book Section
    Additional Information: "©2008 IEEE. Reprinted from IEEE Conference on Computer Communications Workshops, 2008. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE."
    Keywords: adaptive Kalman filters monitoring telecommunication network reliability Adaptive Kalman filtering; Anomaly detection; Failover control; Heartbeat monitoring; Software appliances; INFOCOM; Hamilton Institute. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4544581&isnumber=4544573
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 1751
    Identification Number: https://doi.org/10.1109/INFOCOM.2008.4544581
    Depositing User: Hamilton Editor
    Date Deposited: 15 Dec 2009 15:29
    Publisher: IEEE
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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