Anonymous ID Assignment Used in Privacy Preserving Distributed Data Mining

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Provided by: International Journal of Ethics in Engineering & Management Education (IJEEE)
Topic: Big Data
Format: PDF
In this paper, the authors build an algorithm for sharing simple integer data on top of secure sum data mining operation using Newton's identities and Sturm's theorem. Algorithm for anonymous sharing of private data among parties is developed. This assignment is anonymous in that the identities received are unknown to the other members of the group. Resistance to collusion among other members is verified in an information theoretic sense when private communication channels are used. This assignment of serial numbers allows more complex data to be shared and has applications to other problems in privacy preserving data mining, collision avoidance in communications and distributed database access.
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