Name
Abstract | ||
|---|---|---|
Information and communication technologies bring significant improvements to power grid and help building a “smart grid”. At the same time, they cause novel vulnerabilities making the power grid, which is a critical infrastructure, susceptible to malicious cyber attacks such as false data injection. This paper develops a game-theoretic approach to smart grid security by combining quantitative risk concepts with decision making on protective measures. Specifically, the interaction between malicious attackers and grid defense systems is modeled as a security game, where the attackers choose the intensity of false data injection and defenders determine the detection threshold level. The consequences of data injection attacks are quantified using a risk assessment process based on realistic system simulations. The simulation results are used as an input to a stochastic game model, where the decisions on defensive measures are made taking into account resource constraints represented by cost values. Thus, security games provide a framework for choosing the best response strategies against attackers in order to minimize potential risks. The framework developed is also useful to analyse different types of attacks and defensive measures. The theoretical results obtained are demonstrated using numerical examples. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/Allerton.2012.6483220 | Allerton Conference |
Keywords | DocType | ISSN |
malicious cyber attacks,power system control,critical infrastructures,game-theoretic approach,decision making,smart power grid,critical infrastructure,power system security,stochastic game model,best response strategy,grid defense systems,risk management,smart power grids,false data injection attack,risk assessment process,voltage control,smart grid security,realistic system simulations,stochastic games,security games,detection threshold level,information and communication technologies | Conference | 2474-0195 |
ISBN | Citations | PageRank |
978-1-4673-4537-8 | 1 | 0.37 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yee Wei Law | 1 | 290 | 23.84 |
| Tansu Alpcan | 2 | 1383 | 114.46 |
| M. Palaniswami | 3 | 4107 | 290.84 |