Privacy Preserving Updates Using Generalization-based and Suppression-based K-anonymity
نویسندگان
چکیده
One of the emerging concept in micro data protection is k-anonymity. It permits to assess the risk of disclosure for a data set protected with micro aggregation. Suppose if John owns a k-anonymous database and Kevin wants to insert his own tuple. After insertion if Kevin check the whole database to find out whether anonymity is maintained or not it will violate confidentiality maintained by John. On the other hand if John checks Kevin’s data it will violate privacy. The problem is checking k-anonymity of the database without letting John and Kevin know content of tuple and database. In this paper we propose two protocols namely generalization-based and suppression based kanonymous and confidential databases. These protocols rely on cryptographic assumptions.
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