Detecting False Data Injection Attacks on DC State Estimation
State estimation is an important power system application that is used to estimate the state of the power transmission networks using (usually) a redundant set of sensor measurements and network topology information. Many power system applications such as contingency analysis rely on the output of the state estimator. Until recently it was assumed that the techniques used to detect and identify bad sensor measurements in state estimation can also thwart malicious sensor measurement modification. However, recent work by Liu et al.  demonstrated that an adversary, armed with the knowledge of network configuration, can inject false data into state estimation that uses DC power flow models without being detected. In this work, we explore the detection of false data injection attacks of  by protecting a strategically selected set of sensor measurements and by having a way to independently verify or measure the values of a strategically selected set of state variables. Specifically, we show that it is necessary and sufficient
to protect a set of basic measurements to detect such attacks.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
- The following copyright notice applies to all of the above items that appear in IEEE publications: "Personal use of this material is permitted. However, permission to reprint/publish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from IEEE."
- The following copyright notice applies to all of the above items that appear in ACM publications: "© ACM, effective the year of publication shown in the bibliographic information. This file is the author’s version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in the journal or proceedings indicated in the bibliographic data for each item."
- The following copyright notice applies to all of the above items that appear in IFAC publications: "Document is being reproduced under permission of the Copyright Holder. Use or reproduction of the Document is for informational or personal use only."