Distinct model on privacy protection of dynamic data publication
作者： Xun-yi Ren , Pan Zhang , Yu-qi Zhou
DOI: 10.1007/S10586-018-2506-3
关键词:
摘要: The M-Distinct is an excellent model that supports the anonymization of a fully dynamic set data. This study aimed to explore and analyze model. First all, sensitive values in QI-Group have certain randomness which caused prone be property attacked. However, (M, CUS)-Distinct was proposed required additional records anonymity process. Therefore, its QI-Group-sensitive attribute value must belong same CUS reduce probability attacks. Secondly, involved time cost. creation phase generated disjoint barrel queues ensure each record could stored distribution phase, reduced complexity algorithm. Finally, experiment based on real data sets showed superior terms security, faked processing, execution time.
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