Privacy Preserving Data Mining Using Cryptographic Role Based Access Control Approach

Knowledge is not 'just' information anymore, it is an asset. Data mining is thus extensively used for knowledge discovery from large databases. The problem with data mining is that with the availability of non-sensitive information, sensitive information can be obtained that is not to be disclosed. Thus privacy is becoming an increasingly important issue in many data mining applications. This has led to the development of privacy preserving data mining. Two main approaches/methods to privacy preserving data mining have emerged & applied in recent years. The first approach protects the privacy of the data by using an extended role based access control approach where sensitive objects identification is used to protect an individual's privacy. The second approach uses cryptographic techniques. A new solution by integrating the advantages of both these techniques with the view of minimizing information loss and privacy loss has been used. By making use of cryptographic techniques to store sensitive data and providing access to the stored data based on an individual's role, it is ensured that the data is safe from privacy breaches. In the above mentioned approaches, implementation on privacy preservation in data mining by using the cryptographic role based access control has been done. Here, it is assumed that the decryption occurs entirely at the Server. For real time applications with crucial time-constraints like biomedical applications, the keys for decryption can be distributed to the user for faster decryption and retrieval of data.