TY - JOUR
T1 - Fog-Based Conditional Privacy-Preserving Data Batch Verification in Smart Grid
AU - Liu, Jingwei
AU - Zhao, Mengjiao
AU - Bao, Jiajia
AU - Sun, Rong
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The smart grid is already widespread for the purpose of managing energy generation and distribution. In this system, frequent interactions between devices generate mass data, which requires robust processing capability. Fog computing has the advantage of latency and accessibility that can be applied in smart grids for improving data throughput and energy management efficiency to make the system sustainable. In addition, smart meters (SMs) are responsible for collecting real-time power consumption reports, and then sending them to the service provider (SP). The SP adjusts the power distribution strategy and develops an energy management optimization plan. Unfortunately, this process can reveal sensitive information that the user does not want to disclose. Therefore, we propose a conditional privacy-preserving data aggregation with batch verification scheme. Firstly, as an aggregator, fog devices aggregate masses of data from users into one with simple operation, which reduces communication complexity. Meanwhile, it supports batch verification on the SP side. Secondly, the scheme not only avoids certificates management and key escrow, but implements encrypting and signing in a logical step, thus satisfying confidentiality, integrity and authentication. Finally, our scheme provides conditional privacy-preserving, in which messages can be authenticated anonymously and malicious messages can be traced. Extensive performance evaluation details our scheme is efficient with low computation complexity and communication overheads.
AB - The smart grid is already widespread for the purpose of managing energy generation and distribution. In this system, frequent interactions between devices generate mass data, which requires robust processing capability. Fog computing has the advantage of latency and accessibility that can be applied in smart grids for improving data throughput and energy management efficiency to make the system sustainable. In addition, smart meters (SMs) are responsible for collecting real-time power consumption reports, and then sending them to the service provider (SP). The SP adjusts the power distribution strategy and develops an energy management optimization plan. Unfortunately, this process can reveal sensitive information that the user does not want to disclose. Therefore, we propose a conditional privacy-preserving data aggregation with batch verification scheme. Firstly, as an aggregator, fog devices aggregate masses of data from users into one with simple operation, which reduces communication complexity. Meanwhile, it supports batch verification on the SP side. Secondly, the scheme not only avoids certificates management and key escrow, but implements encrypting and signing in a logical step, thus satisfying confidentiality, integrity and authentication. Finally, our scheme provides conditional privacy-preserving, in which messages can be authenticated anonymously and malicious messages can be traced. Extensive performance evaluation details our scheme is efficient with low computation complexity and communication overheads.
KW - conditional privacy-preserving
KW - fog computing
KW - signcryption
KW - smart grids
UR - http://www.scopus.com/inward/record.url?scp=85184628645&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85184628645&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM46510.2021.9685943
DO - 10.1109/GLOBECOM46510.2021.9685943
M3 - Conference article
AN - SCOPUS:85184628645
SN - 2334-0983
JO - Proceedings - IEEE Global Communications Conference, GLOBECOM
JF - Proceedings - IEEE Global Communications Conference, GLOBECOM
T2 - 2021 IEEE Global Communications Conference, GLOBECOM 2021
Y2 - 7 December 2021 through 11 December 2021
ER -