Cryptography is to become familiar with the requirement of large, complex, information rich data sets for it’s privacy preservation. The privacy preserving data mining has been generated; to go through the concept of privacy in data mining is hard. Several algorithms and approaches are being generated theoretically, but practically it is hard. Privacy in data mining can be achieved through seve...

Large repositories of data contain sensitive information that must be protected against unauthorized access. The protection of the confidentiality of this information has been a long-term goal for the database security research community and for the government statistical agencies. Recent advances in data mining and machine learning algorithms have increased the disclosure risks that one may en...

The field of privacy has seen rapid advances in recent years because of the increases in the ability to store data. In particular, recent advances in the data mining field have lead to increased concerns about privacy. Privacy-preserving data mining has been studied extensively, because of the wide proliferation of sensitive information on the internet. As a result privacy becomes one of the pr...

The recent advancement in data mining technology to analyze vast amount of data has played an important role in several areas of Business processing. Data mining also opens new threats to privacy and information security if not done or used properly. The main problem is that to hide sensitive information, including personal information, fact or even patterns which are generated by any algorithm...

Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data is complete. In order to maintain privacy in the data mining process while cleaning data, privacy-preserving methods of data cleaning are required. In this paper, we address the problem of privacy-preserving data imput...

Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data is complete. In order to maintain privacy in the data mining process while cleaning data, privacy-preserving methods of data cleaning will be required. In this paper, we address the problem of privacy-preserving data i...

Due to the exponential growth of hardware technology particularly in the field of electronic data storage media and processing such data, has raised serious issues related in order to protect the individual privacy like ethical, philosophical and legal. Data mining techniques are employed to ensure the privacy. Privacy Preserving Data Mining (PPDM) techniques aim at protecting the sensitive dat...

The concept of Privacy-Preserving has recently been proposed in response to the concerns of preserving personal or sensible information derived from data mining algorithms. For example, through data mining, sensible information such as private information or patterns may be inferred from non-sensible information or unclassified data. As large repositories of data contain confidential rules that...