NDLI: Behavioral anomaly detection in dynamic self-organizing systems: a cognitive fusion approach

Content Provider	IEEE Xplore Digital Library
Author	Jakobson, G. Lewis, L. Buford, J.
Copyright Year	2005
Description	Author affiliation: Altusys Corp., Brookline, MA, USA (Jakobson, G.)
Abstract	The detection of, and response to, anomalies is one of the prerequisites of implementing system recovery and adaptation mechanisms in dynamic self-organizing systems. In this paper we propose a cognitive fusion approach to the detection of anomalies appearing in the behavior of dynamic self-organizing systems. Our domain of interest includes sensor networks, mobile ad hoc networks, and tactical battle management. The paper argues for three tiers of processes required for behavioral anomaly detection: an event awareness level, a situation awareness level, and a decision awareness level. We discuss self organization in nature and artificial systems and propose an architecture for artificial self-organizing systems that incorporates the three awareness levels. Finally, we propose an application framework in which the architecture could be embodied.
Sponsorship	IEEE Boston Sect
Starting Page	254
Ending Page	259
File Size	477035
Page Count	6
File Format	PDF
ISBN	078039013X
DOI	10.1109/KIMAS.2005.1427090
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-04-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless sensor networks Event detection Disaster management System recovery Sensor phenomena and characterization Large-scale systems Topology Organizing Mobile ad hoc networks Centralized control
Content Type	Text
Resource Type	Article

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