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A recommendation system enables us to take information from huge datasets about tastes effectively. Many cryptographical protocols for computing privacy-preserving recommendation without leaking the privacy of users are proposed. However, the current issue is the large computational overhead depending the number of users. Hence, the application of the protocol is limited within small communities....
We propose a multiparty protocol for various computations using comparator networks such as sorting and searching. By repeating the execution of a comparator, the proposed protocol can efficiently detect outlier values, without revealing them. In our scenario, all input values to a comparator network and the intermediate output from each comparator are kept secret assuming the presence of an honest...
We propose a cryptographic protocol for biometrics authentication without revealing personal biometrical data against malicious verifier. Our protocol uses a neural network and zero-knowledge interactive proof. In this paper, we developed a sample implementation system of our proposed protocol and we evaluate the performance and the accuracy of the proposed protocol. Especially, we study several algorithms...
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