Delay and jitter attacks on hierarchical state estimation. / Baiocco, Alessio; Foglietta, Chiara; Wolthusen, Stephen.

Proceedings of the 2015 IEEE International Conference on Smart Grid Communications. IEEE Press, 2016. p. 485-490.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

State estimation is critical to ensure the stability of
many non-trivial control systems where full observability cannot
be maintained, and is particularly important in electrical power
networks relying on wide-area measurement systems. In recent
years, the problem of malicious bad data injection
has been studied extensively, with a number of innovative mitigation and
protection measures being proposed.
Hierarchical and distributed state estimation systems require
not only correct measurements and means for detecting and
mitigating any faults or attacks, but also
timely transmission of measurements and intermediate results. We argue that the latter has thus far not been considered adequately, and that communication channels cannot be considered to be instantaneous and reliable, nor solely be captured by stochastic models.
In this paper we describe a communication channel model
for hierarchical state estimators relying on the common WLS
formulation and analyse the propagation of faults leading up
to convergence failures in both intermediate and top-level state
estimates as a consequence of interference with the communication channel. To this end we concentrate on denial of service-type attacks, limited to suppression of communication or channel manipulation resulting in delays or jitter as
such attacks are feasible even where channel integrity and confidentiality are
protected adequately. Analytical results showing substantial effects
are supported by simulation results also reported.
Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE International Conference on Smart Grid Communications
PublisherIEEE Press
Pages485-490
DOIs
Publication statusPublished - 21 Mar 2016
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 30327026