Efficient Bucketization Technique for Multidimensional Range Queries over Encrypted Metering Data for Smart Grid

The term “Smart grid” can be described as the next generation electric power system. The metering data should be continuosly examined for valid testing and this is one of the challenge for our smart grid. In this paper we analyze the problem of supporting multidimensional range queries on encrypted metering data. The problem is motivated by the applications of secure data outsourcing where a residential user may store his data on a cloud server in an encrypted form and want to execute queries using server’s computational capabilities. When financial auditing is needed, an authorized requester can send its range query tokens to cloud server to retreive the metering data. The solution approach is to compute a secure indexing tag of the data by applying bucketization(data partitioning) which prevents the cloud server from learning exact values but still allows server to check if a record satisfies the query predicate. Queries are evaluated in an approximate manner where the returned set of records may contain some false positives. In this scheme we can achieve the data confidentiality & query privacy because here only an authorized requester can be able to obtain the query results. Also this approach can significantly reduce communication & computation costs. Keywords— Range query, smart grid, privacy,encrypted data, metering data, outsourcing.