In this article, we introduce a comprehensive framework supporting a privacy-aware access control mechanism, that is, a mechanism tailored to enforce access control to data containing personally identifiable information and, as such, privacy sensitive. The key component of the framework is a family of models (P-RBAC) that extend the well-known RBAC model in order to provide full support for expressing highly complex privacy-related policies, taking into account features like purposes and obligations. We formally define the notion of privacy-aware permissions and the notion of conflicting permission assignments in P-RBAC, together with efficient conflict-checking algorithms. The framework also includes a flexible authoring tool, based on the use of the SPARCLE system, supporting the high-level specification of P-RBAC permissions. SPARCLE supports the use of natural language for authoring policies and is able to automatically generate P-RBAC permissions from these natural language specifications. In the article, we also report performance evaluation results and contrast our approach with other relevant access control and privacy policy frameworks such as P3P, EPAL, and XACML.

The goal of the research study reported here was to investigate policy authors' ability to take descriptions of changes to policy situations and author high-quality, complete policy rules that would parse with high accuracy. As a part of this research, we investigated ways in which we could assist policy authors in writing policies. This paper presents the results of a user study on the effectiveness of providing syntax highlighting in a natural language policy authoring interface. While subjects liked the new interface, they showed no improvement in accuracy when writing rules. We discuss our results in terms of a three phase authoring process that users move through when authoring or modifying policies. We describe this process, discuss why and how our interface failed to support it and make recommendations to designers on how to better support this process.

Privacy policy rules are often written in organizations by a team of people in different roles. Currently, people in these roles have no technological tools to guide the creation of clear and implementable high-quality privacy policy rules. High-quality privacy rules can be the basis for verifiable automated privacy access decisions. An empirical study was conducted with 36 users who were novices in privacy policy authoring to evaluate the quality of rules created and user satisfaction with two experimental privacy authoring tools and a control condition. Results show that users presented with scenarios were able to author significantly higher quality rules using either the natural language with a privacy rule guide tool or a structured list tool as compared to an unguided natural language control condition. The significant differences in quality were found in both user self-ratings of rule quality and objective quality scores. Users ranked the two experimental tools significantly higher than the control condition. Implications of the research and future research directions are discussed.

Today organizations do not have good ways of linking their written privacy policies with the implementation of those policies. To assist organizations in addressing this issue, our humancentered research has focused on understanding organizational privacy management needs, and, based on those needs, creating a usable and effective policy workbench called SPARCLE. SPARCLE will enable organizational users to enter policies in natural language, parse the policies to identify policy elements and then generate a machine readable (XML) version of the policy. In the future, SPARCLE will then enable mapping of policies to the organization’s configuration and provide audit and compliance tools to ensure that the policy implementation operates as intended. In this paper, we present the strategies employed in the design and implementation of the natural

Privacy is a concept which received relatively little attention during the rapid growth and spread of information technology through the 1980's and 1990's. Design to make information easily accessible, without particular attention to issues such as whether an individual had a desire or right to control access to and use of particular information was seen as the more pressing goal. We believe that there will be an increasing awareness of a fundamental need to address privacy concerns in information technology, and that doing so will require an understanding of policies that govern information use as well as the development of technologies that can implement such policies. The research reported here describes our efforts to design a privacy management workbench which facilitates privacy policy authoring, implementation, and compliance monitoring. This case study highlights the work of identifying organizational privacy requirements, analyzing existing technology, on-going research to identify approaches that address these requirements, and iteratively designing and validating a prototype with target users for flexible privacy technologies.