Geometric range search on encrypted spatial data

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Geometric range search on encrypted spatial data +91-9994232214,7806844441, ieeeprojectchennai@gmail.com, www.projectsieee.com, www.ieee-projects-chennai.com IEEE PROJECTS 2016-2017 ----------------------------------- Contact:+91-9994232214,+91-7806844441 Email: ieeeprojectchennai@gmail.com

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Geometric Range Search on Encrypted Spatial Data
Abstract:
Geometric range search is a fundamental primitive for spatial data analysis in SQL
and NoSQL databases. It has extensive applications in location-based services,
computer-aided design, and computational geometry. Due to the dramatic
increase in data size, it is necessary for companies and organizations to outsource
their spatial data sets to third-party cloud services (e.g., Amazon) in order to
reduce storage and query processing costs, but, meanwhile, with the promise of
no privacy leakage to the third party. Searchable encryption is a technique to
perform meaningful queries on encrypted data without revealing privacy.
However, geometric range search on spatial data has not been fully investigated
nor supported by existing searchable encryption schemes. In this paper, we
design a symmetric-key searchable encryption scheme that can support
geometric range queries on encrypted spatial data. One of our major
contributions is that our design is a general approach, which can support different
types of geometric range queries. In other words, our design on encrypted data is
independent from the shapes of geometric range queries. Moreover, we further
extend our scheme with the additional use of tree structures to achieve search
complexity that is faster than linear. We formally define and prove the security of
our scheme with indistinguishability under selective chosen-plaintext attacks, and
demonstrate the performance of our scheme with experiments in a
real cloud platform (Amazon EC2).

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Geometric range search on encrypted spatial data