Dissemination Of Sensitive Data

Defending sensitive data dissemination from adversary's activities like record, attribute, table linkages is an enforcing aspect for better prospects. Existing popular protective measures like k-anonymity and l-diversity perform better in achieving overall data utility maximization by reducing the information loss incurred in the anonymizing process. Unfortunately their strengths are confined to fixed schema data sets with low dimensionality. Earlier two novel anonymization methods such as approximate Nearest-Neighbor (NN) search using Locality-Sensitive Hashing (LSH) and data transformation techniques like reduced band matrix, gray encoded sorting are used to parse high-dimensional spaces.

Provided by: International Journal of Computer Science and Network Security Topic: Data Management Date Added: Jul 2013 Format: PDF

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