Authors:
Mark Dockendorf
and
Ram Dantu
Affiliation:
University of North Texas, 1155 Union Cir, Denton, TX 76203, U.S.A.
Keyword(s):
Data Cooperatives, Privacy, Federated Graph Storage, Applications of Homomorphic Encryption (HE).
Abstract:
Current big data providers offer little-to-no control over how your data is used once it is collected. Data cooperatives are an alternative to these companies and give control of personal data back to the data providers (whether they be people or organizations), allowing them to determine which of their data is used and how their data is used. Data cooperatives can serve as a more ethical alternative to other big data solutions, and have already seen success in the real world. However, supporting software must be developed to ensure the privacy of data providers beyond cooperative promises. In this paper, we expand upon our previous work applying homomorphic encryption (HE) to secure the personally identifiable information (PII) of data providers in data cooperatives that use graph storage. Data cooperatives are expected to store and query over data of varying security levels, including PII, low-security (where anonymization alone is sufficient), and public domain information. To fac
ilitate graph storage, we introduce a multidimensional graph storage technique designed specifically for data cooperatives that mix cleartext, encrypted, and anonymized heterogeneous edges over a heterogeneous set of vertices. We demonstrate a HE query watchdog, which prevents incidental data leakage at query runtime and prior to decryption when proper rules are provided. This watchdog is complementary to existing work preventing data leakage prior to query runtime. This watchdog’s operations are dominated by any reasonably-complex query.
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