Improvement in Privacy and Confidentiality of Database using kACTUS
Harsha V. Talele, Girish Kumar Patnaik · 2014
Today we are living in the heterogeneous world. In this, data privacy and confidentiality is the major issue. Many algorithms are used for data privacy and confidentiality, which are not well-organized because resulted dataset can be simply linked with public database so it reveals user identity. Suppose person-A having his own k-anonymous database and person-B wants to insert a tuple. So, the problem is to check after inserting a tuple whether database retains its k-anonymity or not. If allowing person-A to read content of tuple directly, it breaks the privacy of person-B and on the other hand database confidentiality violated once person-B has access to the contents of the database, so privacy and confidentiality of the database are considered to be a major challenges. If the database is not anonymous with respect to a tuple to be inserted, the insertion cannot be performed and updation is not possible. There are various anonymization technique provides privacy protection which can be used such as data encryption, randomization and k-anonymity. Proposed system uses two manipulation techniques, suppression and generalization which are used to check that if new tuple is being inserted to the dataset it does not affect anonymity of database. The proposed system uses commutative homomorphic encryption scheme to improve data privacy of the database and provides security of data by using AES algorithm. When new tuple is being inserted, updation of database is done easily. It creates kACTUS based server side database for improving k-anonymity. It deals with privacy in anonymous database and on devising private update techniques to database systems that supports notions of anonymity.