Nnprivacy-preserving data publishing a survey of recent developments pdf

Privacy preserving data publishing ppdp methods a new class of privacy preserving data mining. International journal of latest trends in engineering and technology ijltet. Data in its original form, however, typically contains sensitive information about individuals, and publishing such data will violate individual privacy. A new area of research has emerged, called privacy preserving data publishing. The collection of digital information by governments, corporations, and individuals has created tremendous op portunities for knowledge and informationbased decision making.

Data concerning health is a typical example of the type of sensitive information handled in cloud computing environments, and it is obvious that most individuals will want information related to their health to be secure. In other scenarios, the data publisher is interested in the data mining result, but lacks the inhouse expertise to conduct the analysis and, therefore, outsources the data mining activities to some external data miners. In this survey, we will systematically summarize and evaluate different. Privacy preserving data publishing of categorical data through k. Section 8, present the study on various privacy preserving techniques. In other scenarios, the data publisher is interested in the data mining result, but lacks the inhouse expertise to conduct the analysis, and hence outsources the data mining activities to some external data miners. The current practice in data publishing relies mainly on policies and guidelines as to what types of data can be published and on agreements on the use of published data. The proposed literature survey examines the recent. Is achieved by adding random noise to sensitive attribute. This approach alone may lead to excessive data distortion or insufficient protection. Privacy preserving in data publishing is most important research area in data. In the data publishing phase, the data publisher releases the collected data to a data miner or the public, called the data r ecipient, who will then conduct data mining on the published data. Survey result on privacy preserving techniques in data publishing. Driven by mutual benefits, or by regulations that require certain data to.