Although the k-anonymity and ℓ-diversity models have led to a number of valuable privacy-protecting techniques and algorithms, the existing solutions are currently limited to static data release. That is, it is assumed that a complete dataset is avai

Releasing detailed data ( microdata ) about individuals poses a privacy threat, due to the presence of quasi-identifier (QID) attributes such as age or zip code. Several privacy paradigms have been proposed that preserve privacy by placing constraints on the value of released QIDs. However, in order to enforce these paradigms, data publishers need tools to assist them in selecting a suitable anonymization method and choosing the right system parameters. We developed TIAMAT , a tool for analysis of anonymization techniques which allows data publishers to assess the accuracy and overhead of existing anonymization techniques. The tool performs interactive, head-to-head comparison of anonymization techniques, as well as QID change-impact analysis. Other features include collection of attribute statistics, support for multiple information loss metrics and compatibility with commercial database engines.

Integrity has long been considered a fundamental requirement for secure computerized systems, and especially today's demand for data integrity is stronger than ever as many organizations are in-creasing their reliance on data and information systems. A number of recently enacted data privacy regulations also require high in-tegrity for personal data. In this paper, we discuss various issues concerning systematic control and management of data integrity with a primary focus on access control. We first examine some previously proposed integrity models and define a set of integrity requirements. We then present an architecture for comprehensive integrity control systems, which has its basis on data validation and metadata management. We also provide an integrity control policy language that we believe is flexible and intuitive.

As privacy becomes a major concern for both consumers and enterprises, many research efforts have been devoted to the development of privacy protecting technology. We recently proposed a privacy preserving access control model for relational databases,where purpose information associated with a given data element specifies the intended use of the data element. In this paper, we extend our previous work to handle other advanced data managementsystems, such as the ones based on XML and the ones based on the object-relational data model. Another contribution of our paper isthat we address the problem of how to determine the purpose forwhich certain data are accessed by a given user. Our proposedsolution relies on the well-known RBAC model as well as the notionof conditional role which is based on the notions of role attributeand system attribute.