TY - GEN
T1 - PCA based electricity theft detection in advanced metering infrastructure
AU - Singh, Sandeep Kumar
AU - Bose, Ranjan
AU - Joshi, Anupam
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/6/15
Y1 - 2018/6/15
N2 - Advanced metering infrastructure is one of the important components of smart grid and offers an essential link between consumers and their loads, grid, and generation and storage resources. Electricity theft, one of the key concern in AMI, causes million dollar revenue loss every year in developing and developed countries. In this paper, Principal Component Analysis (PCA) based electricity theft detection scheme is proposed. PCA is used to transform a high dimensional dataset into a low dimensional dataset. Using principal components, anomaly score is calculated and compared with a predefined threshold value. The proposed scheme is tested under different attack scenario using real dataset. The results show that the proposed scheme detects electricity theft attacks with high detection rate.
AB - Advanced metering infrastructure is one of the important components of smart grid and offers an essential link between consumers and their loads, grid, and generation and storage resources. Electricity theft, one of the key concern in AMI, causes million dollar revenue loss every year in developing and developed countries. In this paper, Principal Component Analysis (PCA) based electricity theft detection scheme is proposed. PCA is used to transform a high dimensional dataset into a low dimensional dataset. Using principal components, anomaly score is calculated and compared with a predefined threshold value. The proposed scheme is tested under different attack scenario using real dataset. The results show that the proposed scheme detects electricity theft attacks with high detection rate.
KW - Advanced metering infrastructure
KW - cyber security
KW - electricity theft
KW - principal component analysis
UR - http://www.scopus.com/inward/record.url?scp=85049899321&partnerID=8YFLogxK
U2 - 10.1109/ICPES.2017.8387334
DO - 10.1109/ICPES.2017.8387334
M3 - Conference contribution
AN - SCOPUS:85049899321
T3 - 2017 7th International Conference on Power Systems, ICPS 2017
SP - 441
EP - 445
BT - 2017 7th International Conference on Power Systems, ICPS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Power Systems, ICPS 2017
Y2 - 21 December 2017 through 23 December 2017
ER -