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dc.contributor.authorWang, J.
dc.contributor.authorPaschalidis, Ioannis Ch.
dc.date.accessioned2016-08-28T01:34:35Z
dc.date.accessioned2016-08-29T20:08:17Z
dc.date.accessioned2016-09-29T19:21:40Z
dc.date.available2016-09-29T19:21:40Z
dc.date.issued2014-06
dc.identifier.citationJ Wang, I Ch Paschalidis. 2014. "Robust Anomaly Detection in Dynamic Networks." Proceedings of the 22nd Mediterranean Conference on Control and Automation (MED 14), pp. 428 - 433.
dc.identifier.urihttps://hdl.handle.net/2144/18020
dc.description.abstractWe propose two robust methods for anomaly detection in dynamic networks in which the properties of normal traffic evolve dynamically. We formulate the robust anomaly detection problem as a binary composite hypothesis testing problem and propose two methods: a model-free and a model-based one, leveraging techniques from the theory of large deviations. Both methods require a family of Probability Laws (PLs) that represent normal properties of traffic. We devise a two-step procedure to estimate this family of PLs. We compare the performance of our robust methods and their vanilla counterparts, which assume that normal traffic is stationary, on a network with a diurnal normal pattern and a common anomaly related to data exfiltration. Simulation results show that our robust methods perform better than their vanilla counterparts in dynamic networks.en_US
dc.format.extent428 - 433en_US
dc.relation.ispartofProceedings of the 22nd Mediterranean Conference on Control and Automation (MED 14)en_US
dc.relation.ispartofseriesProceedings of the 22nd Mediterranean Conference on Control and Automation;
dc.relation.replaceshttp://hdl.handle.net/2144/17762
dc.relation.replaces2144/17762
dc.relation.replaceshttp://hdl.handle.net/2144/17763
dc.relation.replaces2144/17763
dc.rightsAttribution 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectNetworking and Internet Architecture (cs.NI)en_US
dc.subjectApplications (stat.AP)en_US
dc.subjectRobust statistical anomaly detectionen_US
dc.subjectProbability lawsen_US
dc.subjectStatistical testingen_US
dc.titleRobust anomaly detection in dynamic networksen_US
dc.typeArticleen_US
dc.typeConference materialsen_US
dc.identifier.doi10.1109/MED.2014.6961410
pubs.notesEmbargo: No embargoen_US
pubs.organisational-group/Boston University
pubs.organisational-group/Boston University/College of Engineering
pubs.organisational-group/Boston University/College of Engineering/Department of Electrical & Computer Engineering


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Except where otherwise noted, this item's license is described as Attribution 4.0 International