ECQ: An Efficient Conjunctive Query scheme over encrypted multidimensional data in smart grid

With the deployment of smart meters at individual households, smart grid can collect metering data of users' power consumption. However, users' power usage patterns would also be revealed. To preserve the users' privacy, metering data is mostly encrypted by cryptographic algorithms. When data mining is needed to support decision making or ensure reliability, to find useful information from the encrypted data is very important for smart grid. Most of the traditional keyword searching schemes rarely consider both users' data privacy and requesters' query privacy. In particular, the power system data in smart grid has multidimensional attributes; thus, how to query over the encrypted multidimensional data on all dimensions is a challenging issue in smart grid. To achieve finer grained conjunctive query, this paper proposes an Efficient Conjunctive Query (ECQ) scheme. Specificly, the ECQ incorporates the idea of public key encryption and conjunctive keywords search to achieve conjunctive query without data and query privacy leakage. Security analysis demonstrates that the ECQ can achieve the security requirements, namely, data confidentiality, integrity and privacy, as well as query privacy. In addition, simulation results show that the ECQ can reduce users' computation cost and total communication cost.