Systems and methods for condensation-based privacy in strings

Details Systems and methods for condensation-based privacy in strings Systems and methods for condensation-based privacy in strings

2011-08-30

2011-08-30

Kim, Charles (Department: 2157)

Data processing: database and file management or data structures

Database and file access

Preparing data for information retrieval

Reexamination Certificate

active

08010541

ABSTRACT:
Novel methods and systems for the privacy preserving mining of string data with the use of simple template based models. Such template based models are effective in practice, and preserve important statistical characteristics of the strings such as intra-record distances. Discussed herein is the condensation model for anonymization of string data. Summary statistics are created for groups of strings, and use these statistics are used to generate pseudo-strings. It will be seen that the aggregate behavior of a new set of strings maintains key characteristics such as composition, the order of the intra-string distances, and the accuracy of data mining algorithms such as classification. The preservation of intra-string distances is a key goal in many string and biological applications which are deeply dependent upon the computation of such distances, while it can be shown that the accuracy of applications such as classification are not affected by the anonymization process.

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