Privacy Issues and Preservation

Privacy Issues and Preservation

Preserving data privacy is a growing challenge for database security and privacy experts. In some perspectives, to preserve data privacy we should even limit per-forming large-scale data mining and analysis. The most commonly used techniques to address this concern are to avoid building mammoth central warehouses as a single repository of vital information. Another possible measure is to intentionally modify or perturb data.

If all data were available at a single warehouse, violating only a single repository’s security could expose all data. Avoiding central warehouses and using distributed data mining algorithms minimizes the exchange of data needed to develop globally valid models. By modifying, perturbing, and anonymizing data, we can also mitigate privacy risks associated with data mining. This can be done by removing identity information from the released data and injecting noise into the data. However, by using these techniques, we should pay attention to the quality of the resulting data in the database, which may undergo too many modifications. We must be able to estimate the errors that may be introduced by these modifications.

Privacy is an important area of ongoing research in database management. It is complicated due to its multidisciplinary nature and the issues related to the subjectivity in the interpretation of privacy, trust, and so on. As an example, consider medical and legal records and transactions, which must maintain certain privacy requirements while they are being defined and enforced. Providing access control and privacy for mobile devices is also receiving increased attention. DBMSs need robust techniques for efficient storage of security-relevant information on small devices, as well as trust negotiation techniques. Where to keep information related to user identities, profiles, credentials, and permissions and how to use it for reliable user identification remains an important problem. Because large-sized streams of data are generated in such environments, efficient techniques for access control must be devised and integrated with processing techniques for continuous queries. Finally, the privacy of user location data, acquired from sensors and communication networks, must be ensured.