MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Efficient NP Tests for Anomaly Detection Over Birth-Death Type DTMCs

Author(s)
Ozkan, Huseyin; Ozkan, Fatih; Delibalta, Ibrahim; Kozat, Suleyman S.
Thumbnail
Download11265_2016_1147_ReferencePDF.pdf (392.0Kb)
PUBLISHER_POLICY

Publisher Policy

Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

Terms of use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Metadata
Show full item record
Abstract
We propose computationally highly efficient Neyman-Pearson (NP) tests for anomaly detection over birth-death type discrete time Markov chains. Instead of relying on extensive Monte Carlo simulations (as in the case of the baseline NP), we directly approximate the log-likelihood density to match the desired false alarm rate; and therefore obtain our efficient implementations. The proposed algorithms are appropriate for processing large scale data in online applications with real time false alarm rate controllability. Since we do not require parameter tuning, our algorithms are also adaptive to non-stationarity in the data source. In our experiments, the proposed tests demonstrate superior detection power compared to the baseline NP while nearly achieving the desired rates with negligible computational resources. Keywords: Anomaly detection, Neyman pearson, NP, False alarm, Efficient Online, Markov DTMC
Date issued
2016-06
URI
http://hdl.handle.net/1721.1/117017
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Journal
Journal of Signal Processing Systems
Publisher
Springer US
Citation
Ozkan, Huseyin, et al. “Efficient NP Tests for Anomaly Detection Over Birth-Death Type DTMCs.” Journal of Signal Processing Systems, vol. 90, no. 2, Feb. 2018, pp. 175–84.
Version: Author's final manuscript
ISSN
1939-8018
1939-8115

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.