TY - GEN
T1 - Spatio-Temporal Synchrophasor Data Characterization for Mitigating False Data Injection in Smart Grids
AU - Cui, Yi
AU - Wang, Weikang
AU - Liu, Yilu
AU - Fuhr, Peter
AU - Morales-Rodriguez, Marissa
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - As electric power grids' dependence on wide area monitoring systems (WAMS) is expected to increase significantly in the near future, the cyber security concerns of WAMS must be carefully addressed. False data injection attack (FDIA) is a typical cyber-physical attack of WAMS in modern smart grids. This paper presents a data mining-based approach to identify FDIA on frequency data of WAMS by revealing the spatio-temporal signatures of synchrophasor measurements. Specifically, recurrence quantification analysis (RQA) is utilized to extract temporal signatures of frequency measurements while the spatial signatures are derived by using statistical method. Three FDIA scenarios, i.e., 'Source ID Mix', time mirroring and time dilation attacks are simulated. Experimental results by using synchrophasor measurements archived in FNET /GridEye demonstrate the practicability of the proposed methodology for mitigating FDIA on frequency measurements of power systems.
AB - As electric power grids' dependence on wide area monitoring systems (WAMS) is expected to increase significantly in the near future, the cyber security concerns of WAMS must be carefully addressed. False data injection attack (FDIA) is a typical cyber-physical attack of WAMS in modern smart grids. This paper presents a data mining-based approach to identify FDIA on frequency data of WAMS by revealing the spatio-temporal signatures of synchrophasor measurements. Specifically, recurrence quantification analysis (RQA) is utilized to extract temporal signatures of frequency measurements while the spatial signatures are derived by using statistical method. Three FDIA scenarios, i.e., 'Source ID Mix', time mirroring and time dilation attacks are simulated. Experimental results by using synchrophasor measurements archived in FNET /GridEye demonstrate the practicability of the proposed methodology for mitigating FDIA on frequency measurements of power systems.
KW - Cyber-physical attack
KW - smart grid
KW - spatiotemporal signature
KW - synchrophasor
KW - wide area monitoring systems
UR - http://www.scopus.com/inward/record.url?scp=85079072891&partnerID=8YFLogxK
U2 - 10.1109/PESGM40551.2019.8973586
DO - 10.1109/PESGM40551.2019.8973586
M3 - Conference contribution
AN - SCOPUS:85079072891
T3 - IEEE Power and Energy Society General Meeting
BT - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019
PB - IEEE Computer Society
T2 - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Y2 - 4 August 2019 through 8 August 2019
ER -