Alese BK and Adebayo OT
Sharing genomic is important for healthcare but privacy must be protected because links between de-identified genomic data and named persons can be re-established by users with malicious intents. In this paper, a game theoretic approach is developed for quantifiable protections of genomic data sharing. This approach accounts for adversarial behavior and capabilities. The game model is developed to discover the best solution for sharing genomic summary statistics under an economically driven recipient’s (adversary) inference attack based on a Stackelberg game. The inference attack checks if a targeted DNA is in a genome pool with published summary statistics (that is, minor allele frequency of Single Nucleic Polymorphisms).
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