What is it about?
It presents a computational technique that leverages the asymptotic-stabilization behavior of transition probabilities that are characterized by two-state Markov chain. These asymptotic probabilities help the computational technique to protect the privacy of the functional magnetic resonance imaging (fMRI) data that is shared over a public distributed computer network.
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This page is a summary of: Asymptotically Stable Privacy Protection Technique for fMRI Shared Data over Distributed Computer Networks, September 2020, ACM (Association for Computing Machinery),
DOI: 10.1145/3388440.3414863.
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