PARQ BASED RANGE QUERYPREDICATE IN GRID COMPUTING
International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC).
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Smart grid, envisioned as an indispensable power infrastructure, is featured by real-time and two-way communications. How to securely retrieve and audit the communicated metering data for validation testing is, however, still challenging for smart grid. In this paper, we propose a novel privacy-preserving range query (PaRQ) scheme over encrypted metering data to address the privacy issues in financial auditing for smart grid. Our PaRQ allows a residential user to store metering data on a cloud server in an encrypted form. When financial auditing is needed, an authorized requester can send its range query tokens to the cloud server to retrieve the metering data. Specifically, the PaRQ constructs a hidden vector encryption based range query predicate to encrypt the searchable attributes and session keys of the encrypted data. Meanwhile, the requester's range query can be transferred into two query tokens, which are used to find the matched query results. Security analysis demonstrates that in the PaRQ, only the authorized requesters can obtain the query results, while the data confidentiality and query privacy are also preserved. The simulation results show that our PaRQ can significantly reduce communication and computation costs.
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Privacy, Smart Grid, Statistics, Aggregation, Stream, Fault-Tolerance