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In this project, we address three potential challenges for secure sharing and count query execution on the genomic data: data privacy, query privacy, and output privacy.

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Secure-Count-Query-on-Encrypted-Biomedical-Data

We designed a secure framework for outsourcing genomic data and executing count query on it. Count query determines the number of records in the database that match a query predicate and it is very useful for genetic association studies to compute several statistical algorithms.

Count query is a simple and straightforward operation if the data is stored in plaintext and traditional database management systems (DBMS) support a built-in operation for it. However, these DBMSs are not designed to execute count query operation on the encrypted data.

We used a tree-based indexing algorithm to pre-filter the search result. Execution of a query is done by traversing an encrypted tree where the decision of traversing each node is made by checking whether a query predicate matches with a particular branch of the tree.

Technologies: Java, MySQL

Project Owners: Zahidul Hasan, Safiur Mahdi, Noman Mohammed

License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License

Publication: Z. Hasan, MSR. Mahdi, MN. Sadat and N. Mohammed – Secure Count Query on Encrypted Genomic Data – Journal of Biomedical Informatics (JBI), vol. 81, pp. 41-52, 2018

Disclaimer: The software is provided as-is with no warranty or support. We do not take any responsibility for any damage, loss of income, or any problems you might experience from using our software. If you have questions, you are encouraged to consult the paper and the source code. If you find our software useful, please cite our paper above.

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In this project, we address three potential challenges for secure sharing and count query execution on the genomic data: data privacy, query privacy, and output privacy.

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