EPLQ: Efficient Privacy-Preserving Location-Based Query Over Outsourced Encrypted Data
Efficient Privacy-Preserving Location Protecting mobile user location information in Location Based Services is a very important but difficult and still largely unsolved issue.projects on Efficient Privacy-Preserving Location.
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Projects on Efficient Privacy-Preserving Location Querying encrypted LBS data without privacy breach is a big challenge, and we need to protect not only the user locations from the LBS provider and cloud, but also LBS data from the cloud.
The cryptographic or privacy-enhancing techniques used to realize privacy-preserving query usually result in high computational cost and/or storage cost at user side.
Efficient privacy-preserving location-based query over outsourced encrypted data paper, we have proposed EPLQ, an efficient smartphone spatial range query solution that preserves user location privacy and ensures the confidentiality of LBS data.
Realize EPLQ, we designed an IPRE and a novel, privacy-preserving index tree called ss-tree. EPLQ’s effectiveness has been evaluated with theoretical analysis and experiments, and detailed analysis shows its security against known-sample attacks and text-only cipher attacks.
Projects reports on Efficient Privacy Our techniques have potential uses in other kinds of queries that preserve privacy. If the query can be performed by comparing internal products to a given range, the proposed IPRE and ss-tree may be applied to perform privacy-conserving query.Two potential uses are queries of similarities preserving privacy and long spatial range queries. We will be designing solutions for these scenarios in the future and identifying more uses.