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Model-based analysis of 'k out of m' correlation techniques for diverse redundant detectors
Ansaldo STS, Italy.ORCID iD: 0000-0002-2833-7196
2013 (English)In: International Journal of Performability Engineering, ISSN 0973-1318, Vol. 9, no 5, p. 551-560Article in journal (Refereed) Published
Abstract [en]

Sensors are widespread in applications ranging from environmental monitoring to distributed surveillance for physical security. Novel protocols and appropriate topologies enable large networks of cheap smart-sensors with the main objective of providing pervasiveness and resilience. In this paper we provide a model-based analysis of a 'k-out-of-m' ('KooM') voting approach which can be used to correlate data coming from heterogeneous event detecting devices. The approach is based on the assumption of diverse redundancy on sensor technologies. The Bayesian Network formalism is employed to perform the analysis. The results show that by choosing appropriate correlation logics an optimal trade-off can be achieved among probability of detection, false alarm rate, availability and robustness against spoofing attempts, depending on the specific application. Furthermore, it will be shown that majority voting on detector outputs allows for a high cost effectiveness in obtaining performance improvements. © RAMS Consultants.

Place, publisher, year, edition, pages
RAMS Consultants , 2013. Vol. 9, no 5, p. 551-560
Keywords [en]
Bayesian networks, Diverse redundancy, Multi-sensor decision fusion, Physical security, Quantitative evaluation, Stochastic modeling, Voting, Sensors, Stochastic models, Decision fusion
National Category
Embedded Systems
Research subject
Computer Science, Software Technology
Identifiers
URN: urn:nbn:se:lnu:diva-73662Scopus ID: 2-s2.0-84897495698OAI: oai:DiVA.org:lnu-73662DiVA, id: diva2:1213307
Available from: 2018-06-04 Created: 2018-06-04 Last updated: 2018-06-05Bibliographically approved

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Flammini, Francesco

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  • sv-SE
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