Publishing the data with multiple sensitive attributes brings us greater challenge than publishing the data with single sensitive attribute in the area of privacy preserving. In this study, we propose a novel privacy preserving model based on k-anonymity called (α, β, k)-anonymity for databases. (α, β, k)anonymity can be used to protect data with multiple sensitive attributes in data publishing...

The problem of the release of anonymized microdata is an important topic in the fields of statistical disclosure control (SDC) and privacy preserving data publishing (PPDP), and yet it remains sufficiently unsolved. In these research fields, k-anonymity has been widely studied as an anonymity notion for mainly deterministic anonymization algorithms, and some probabilistic relaxations have been ...

Identity disclosure is one of the most serious privacy concerns in today’s information age. A well-know method, called k-anonymity, has recently been proposed and used to protect identity disclosure. The k-anonymity approach, however, still allows a data intruder to discern the confidential information in the anonymized data. To overcome this problem, we propose a data reconstruction approach, ...

When a private relational table is published using views, secrecy or privacy may be violated. This paper uses a formally-defined notion of k-anonymity to measure disclosure by views, where k>1 is a positive integer. Intuitively, violation of k-anonymity occurs when a particular attribute value of an entity can be determined to be among less than k possibilities by using the views together with ...

Today’s globally networked society places great demand on the dissemination and sharing of information. While in the past released information was mostly in tabular and statistical form, many situations call today for the release of specific data (microdata). In order to protect the anonymity of the entities (called respondents) to which information refers, data holders often remove or encrypt ...

k-anonymity provides a measure of privacy protection by preventing re-identification of data to fewer than a group of k data items. While algorithms exist for producing k-anonymous data, the model has been that of a single source wanting to publish data. This paper presents a k-anonymity protocol when the data is vertically partitioned between sites. A key contribution is a proof that the proto...

Anonymization techniques are used to ensure the privacy preservation of the data owners, especially for personal and sensitive data. While in most cases, data reside inside the database management system; most of the proposed anonymization techniques operate on and anonymize isolated datasets stored outside the DBMS. Hence, most of the desired functionalities of the DBMS are lost, e.g., consist...