Malicious data detection and localization in state estimation leveraging system losses

In power systems, economic dispatch, contingency analysis, and the detection of faulty equipment rely on the output of the state estimator. Typically, state estimations are made based on the network topology information and the measurements from a set of sensors within the network. The state estimates must be accurate even with the presence of corrupted measurements. Traditional techniques used to detect and identify bad sensor measurements in state estimation cannot thwart malicious sensor measurement modifications, such as malicious data injection attacks. Recent work by Niemira (2013) has compared real and reactive injection and flow measurements as indicators of attacks. In this work, we improve upon the method used in that work to further enhance the detectability of malicious data injection attacks, and to incorporate PMU measurements to detect and locate previously undetectable attacks.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Lu, Miao

• false data injection
• phasor measurement units
• state estimation
• power system cyber security

Statement dc:rights

• Copyright 2015 Miao Lu

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/78661

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/78661