Affiliation:
1. Purdue University, Lafayette, IN
2. IBM T. J. Watson, Hawthorne, NY
3. Insubria University, Varese, Italy
Abstract
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.
Funder
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Safety, Risk, Reliability and Quality,General Computer Science
Cited by
114 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献