Multidimensional data tight aggregation and fine-grained access control in smart grid

Abstract

In smart grid, for saving communication bandwidth and performing fine-grained analysis, the power data need to be collected and aggregated in multi-dimensions. As each dimension contains sensitive information of users and may be used by different analytic organizations, privacy preserving and access control for multidimensional power data are obviously important. Existing schemes either cannot support dimensional access control or require transmitting attribute sets of data together with ciphertexts, which leaks the relevant information of power data and increases the security risk. Moreover, to disseminate and implement access control of the multidimensional data, control center (CC) must firstly decrypt the data of all dimensions, which may result in the data leakage. In this paper, we propose a Multidimensional-data Tight Aggregation scheme which supports Privacy preserving and fine-grained Access control (MTA–PA). In MTA–PA, we import the extended Boneh–Goh–Nissim (EBGN) homomorphic encryption from wireless sensor networks to aggregate multidimensional power data into one ciphertext and simultaneously use key-policy attribute-based encryption (KP–ABE) to enforce fine-grained access control at the dimension level. By using MTA–PA, the gateway need not to distinguish different ciphertexts before aggregating them, and organizations only can analyze the authorized dimensions of power data. MTA–PA further achieves secure access-permission update via updating related parameters of EBGN and KP–ABE. And then, we also present the implementation methods of the algorithms. The security analysis and experimental results show that MTA–PA is a secure and efficient data protection scheme in smart grid.