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A Robust Privacy Preserving of Multiple and Binary Attribute by Using Super Modularity with Perturbation
2018
International Journal of Scientific Research in Computer Science Engineering and Information Technology
With the increase of digital data on servers different approach of data mining is applied for the retrieval of interesting information in decision making. A major social concern of data mining is the issue of privacy and data security. So privacy preserving mining come in existence, as it validates those data mining algorithms that do not disclose sensitive information. This work provides privacy for sensitive rules that discriminate data on the basis of community, gender, country, etc. Rules
doi:10.32628/cseit183838
fatcat:jkg6uoaddrexlpkrbl6b2qb7h4