Abstract
This paper studies physical consequences of worst-case unobservable false data injection (FDI) attacks on the electric power system. In particular the focus is on FDI attacks wherein the attacker can only change measurements in an attack sub-network of the entire network and has limited knowledge of network parameters outside of this sub-network. The goal of this limited resource attack is to cause a physical line overflow for a chosen target line that will not be observable via measurements. To determine the worst possible consequences of such a class of FDI attacks, a bi-level optimization problem is introduced wherein the first level focuses on maximizing the target line flow subject to limited attack resources constraints, while the second level formulates system response to such attacks via DC optimal power flow (OPF). The attack model with limited system knowledge is reflected in the DC OPF formulation that only takes into account the system information for the attack sub-network and therefore is oblivious of congestion and data for the network outside this sub-network. The vulnerability of this attack model is illustrated for the IEEE 24-bus RTS system.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 |
| Publisher | IEEE Computer Society |
| Volume | 2016-November |
| ISBN (Electronic) | 9781509041688 |
| DOIs | |
| State | Published - Nov 10 2016 |
| Event | 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 - Boston, United States Duration: Jul 17 2016 → Jul 21 2016 |
Other
| Other | 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 |
|---|---|
| Country | United States |
| City | Boston |
| Period | 7/17/16 → 7/21/16 |
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ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Nuclear Energy and Engineering
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
Cite this
False data injection attacks on power system state estimation with limited information. / Zhang, Jiazi; Chu, Zhigang; Sankar, Lalitha; Kosut, Oliver.
2016 IEEE Power and Energy Society General Meeting, PESGM 2016. Vol. 2016-November IEEE Computer Society, 2016. 7741928.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - False data injection attacks on power system state estimation with limited information
AU - Zhang, Jiazi
AU - Chu, Zhigang
AU - Sankar, Lalitha
AU - Kosut, Oliver
PY - 2016/11/10
Y1 - 2016/11/10
N2 - This paper studies physical consequences of worst-case unobservable false data injection (FDI) attacks on the electric power system. In particular the focus is on FDI attacks wherein the attacker can only change measurements in an attack sub-network of the entire network and has limited knowledge of network parameters outside of this sub-network. The goal of this limited resource attack is to cause a physical line overflow for a chosen target line that will not be observable via measurements. To determine the worst possible consequences of such a class of FDI attacks, a bi-level optimization problem is introduced wherein the first level focuses on maximizing the target line flow subject to limited attack resources constraints, while the second level formulates system response to such attacks via DC optimal power flow (OPF). The attack model with limited system knowledge is reflected in the DC OPF formulation that only takes into account the system information for the attack sub-network and therefore is oblivious of congestion and data for the network outside this sub-network. The vulnerability of this attack model is illustrated for the IEEE 24-bus RTS system.
AB - This paper studies physical consequences of worst-case unobservable false data injection (FDI) attacks on the electric power system. In particular the focus is on FDI attacks wherein the attacker can only change measurements in an attack sub-network of the entire network and has limited knowledge of network parameters outside of this sub-network. The goal of this limited resource attack is to cause a physical line overflow for a chosen target line that will not be observable via measurements. To determine the worst possible consequences of such a class of FDI attacks, a bi-level optimization problem is introduced wherein the first level focuses on maximizing the target line flow subject to limited attack resources constraints, while the second level formulates system response to such attacks via DC optimal power flow (OPF). The attack model with limited system knowledge is reflected in the DC OPF formulation that only takes into account the system information for the attack sub-network and therefore is oblivious of congestion and data for the network outside this sub-network. The vulnerability of this attack model is illustrated for the IEEE 24-bus RTS system.
UR - http://www.scopus.com/inward/record.url?scp=85001871756&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85001871756&partnerID=8YFLogxK
U2 - 10.1109/PESGM.2016.7741928
DO - 10.1109/PESGM.2016.7741928
M3 - Conference contribution
AN - SCOPUS:85001871756
VL - 2016-November
BT - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016
PB - IEEE Computer Society
ER -