1. Outsourcing Medical Dataset Analysis: A Possible Solution 2017 FHE FinancialCryptography medical
    Gabriel Kaptchuk, Matthew Green, Aviel Rubin
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    [Show BibTex Citation]

    @inproceedings{DBLP:conf/fc/Kaptchuk0R17,
    author = {Gabriel Kaptchuk and
    Matthew Green and
    Aviel D. Rubin},
    editor = {Aggelos Kiayias},
    title = {Outsourcing Medical Dataset Analysis: {A} Possible Solution},
    booktitle = {Financial Cryptography and Data Security - 21st International Conference,
    {FC} 2017, Sliema, Malta, April 3-7, 2017, Revised Selected Papers},
    series = {Lecture Notes in Computer Science},
    volume = {10322},
    pages = {98--123},
    publisher = {Springer},
    year = {2017},
    url = {https://doi.org/10.1007/978-3-319-70972-7\_6},
    doi = {10.1007/978-3-319-70972-7\_6},
    timestamp = {Tue, 14 May 2019 10:00:38 +0200},
    biburl = {https://dblp.org/rec/bib/conf/fc/Kaptchuk0R17},
    bibsource = {dblp computer science bibliography, https://dblp.org}
    }

We explore the possible ways modern cryptographic methodscan be applied to the field of medical data analysis. Current systems require large computational facilities owned by the data owners or excessive trust given to the researchers. We implement one possible solution inwhich researchers operate directly on homomorphically encrypted data and the data owner decrypts the results. We test our implementation on large datasets and show that it is sufficiently practical that it could be a helpful tool for modern researchers. We also perform a heuristic analysis of the security of our system.

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