Show simple item record

Attack-Resilient State Estimation in the Presence of Noise

dc.contributor.author Pajic, M
dc.contributor.author Tabuada, P.
dc.contributor.author Lee, I.
dc.contributor.author Pappas, G.J.
dc.coverage.spatial Osaka, Japan
dc.date.accessioned 2015-12-29T03:02:26Z
dc.identifier.uri https://hdl.handle.net/10161/11286
dc.description.abstract We consider the problem of attack-resilient state estimation in the presence of noise. We focus on the most general model for sensor attacks where {any} signal can be injected via the compromised sensors. An $l_0$-based state estimator that can be formulated as a mixed-integer linear program and its convex relaxation based on the $l_1$ norm are presented. For both $l_0$ and $l_1$-based state estimators, we derive rigorous analytic bounds on the state-estimation errors. We show that the worst-case error is linear with the size of the noise, meaning that the attacker cannot exploit noise and modeling errors to introduce unbounded state-estimation errors. Finally, we show how the presented attack-resilient state estimators can be used for sound attack detection and identification, and provide conditions on the size of attack vectors that will ensure correct identification of compromised sensors.
dc.source 54th IEEE Conference on Decision and Control (CDC)
dc.title Attack-Resilient State Estimation in the Presence of Noise
dc.type Conference
duke.contributor.id Pajic, M|0662016
pubs.begin-page 527
pubs.end-page 532
pubs.finish-date 2015-12-18
pubs.organisational-group Computer Science
pubs.organisational-group Duke
pubs.organisational-group Electrical and Computer Engineering
pubs.organisational-group Pratt School of Engineering
pubs.organisational-group Trinity College of Arts & Sciences
pubs.start-date 2015-12-15


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record