A Secure and Flexible Data Aggregation Framework for Smart Grid
Smart grids are electrical grids that take advantage of information and communication technologies to achieve energy-efficiency, automation and reliability. Smart grids include renewable energy, electrical vehicles, phasor measurement unit (PMU) and advanced metering infrastructure system (AMI) etc. The system’s availability can be achieved via data aggregation technique by reducing the overhead of networks. However, since smart grids have become more popular in recent years, many researches have been done on the security issue of the smart grid such as confidentiality, integrity and availability. For these security issues, many researchers adopt secure data aggregation algorithms to protect the data transmission and to reduce the overhead of networks. In this paper, we propose a secure data aggregation framework, which provides multi-level security for different kinds of applications.
KeywordsSmart grid Data aggregation
The authors would like to thank anonymous reviewers for their valuable comments and suggestions that certainly led to improvements of this paper. This research was partially supported by the National Science Council of the Republic of China under Contract NSC-101-2221-E-007-026-MY3 and NSC-100-2628-E-007-018-MY3. The corresponding author is Professor Hung-Min Sun.
- 1.Elsters proposal for privacy enhancing technology implementation. http://www.elster.com/en/privacy-enhancing-technologies-for-the-smart-grid
- 2.Kamto J, Qian L, Fuller J, Attia J, Qian Y (2012) Key distribution and management for power aggregation and accountability in advance metering infrastructure. In: Smart grid communications (SmartGridComm), 2012 IEEE international conferenceGoogle Scholar
- 3.Khurana H, Hadley M, Lu N, Frincke D (2010) Smart-grid security issues. Secur Priv IEEE 8(1):81–85Google Scholar
- 4.Li F, Luo B, Liu P (2010) Secure information aggregation for smart grids using homomorphic encryption. In: Smart grid communications (SmartGridComm), 2010 first IEEE international conference, pp 327–332Google Scholar
- 11.Li F, Luo B (2012) Preserving data integrity for smart grid data aggregation. In: Smart grid communications (SmartGridComm), IEEE third international conference, pp 366–371Google Scholar
- 5.Lin H, Deng Y, Shukla S, Throp J, Mili L (2012) Cyber security impacts on all-pmu state estimator: a case study on co-simulation platform GECO. In: Smart grid communications (SmartGridComm), 2012 IEEE international conference. pp 587–592Google Scholar
- 6.Deamen J, Rijmen V (1998) AES proposal: Rijndael. In: First advanced encryption standard (AES) conferenceGoogle Scholar
- 7.Lu R, Liang X, Li X, Lin X, Shen X (2012) EPPA: an efficient and privacy-preserving aggregation scheme for secure smart grid communications. Parallel Distrib Syst IEEE Trans 23(9):1621–1631Google Scholar
- 8.Metke A, Ekl R (2010) Security technology for smart grid networks. Smart Grid IEEE Trans 1(1):99–107Google Scholar
- 9.Parikh P, Kanabar M, Sidhu T (2010) Opportunities and challenges of wireless communication technologies for smart grid applications. In: Power and energy society general meeting, 2010 IEEE. pp 1–7Google Scholar