Secure data aggregation with privacy-protection in smart grid

2015 ◽  
pp. 77-84
Keyword(s):  
Smart Grid ◽  
Data Aggregation ◽  
Privacy Protection ◽  
Secure Data ◽  
Secure Data Aggregation

scholarly journals FESDA: Fog-Enabled Secure Data Aggregation in Smart Grid IoT Network

2020 ◽  
Vol 7 (7) ◽  
pp. 6132-6142 ◽  
Author(s):  
Ahsan Saleem ◽  
Abid Khan ◽  
Saif Ur Rehman Malik ◽  
Haris Pervaiz ◽  
Hassan Malik ◽  
...  
Keyword(s):  
Smart Grid ◽  
Data Aggregation ◽  
Secure Data ◽  
Secure Data Aggregation

scholarly journals Efficient and Privacy-Preserving Data Aggregation and Dynamic Billing in Smart Grid Metering Networks

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2085 ◽  
Author(s):  
An Braeken ◽  
Pardeep Kumar ◽  
Andrew Martin
Keyword(s):  
Smart Grid ◽  
Data Aggregation ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Smart Meters ◽  
Life Patterns ◽  
Consumption Data ◽  
Secure Data ◽  
Secure Data Aggregation ◽  
Privacy Issues

The smart grid enables convenient data collection between smart meters and operation centers via data concentrators. However, it presents security and privacy issues for the customer. For instance, a malicious data concentrator cannot only use consumption data for malicious purposes but also can reveal life patterns of the customers. Recently, several methods in different groups (e.g., secure data aggregation, etc.) have been proposed to collect the consumption usage in a privacy-preserving manner. Nevertheless, most of the schemes either introduce computational complexities in data aggregation or fail to support privacy-preserving billing against the internal adversaries (e.g., malicious data concentrators). In this paper, we propose an efficient and privacy-preserving data aggregation scheme that supports dynamic billing and provides security against internal adversaries in the smart grid. The proposed scheme actively includes the customer in the registration process, leading to end-to-end secure data aggregation, together with accurate and dynamic billing offering privacy protection. Compared with the related work, the scheme provides a balanced trade-off between security and efficacy (i.e., low communication and computation overhead while providing robust security).

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