Email this article An Algorithm Of Anonymous Id Assignment For Secure Data Sharing On A Network
Abstract
Existing and new algorithms for assigning anonymous IDs are scrutinized with respect to trade-offs among communication and computational requirements. An algorithm for distributed solution of certain polynomials over limited fields improves the scalability of the algorithms. Another form of anonymity as used in secure multiparty computation allows multiple parties on a network to together carry out a global computation that depends on data from each party while the data supposed by each party remains unknown to the other parties. The new algorithms are constructed on top of a secure sum data mining operation using Newton’s identities and Sturm’s theorem. An algorithm for distributed solution of convinced polynomials over limited fields improves the scalability of the algorithms. Markov chain representations are used to find statistics on the number of iterations required and computer algebra gives closed form results for the completion rates.
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