Low-Resource Speech Recognition of 500-Word Vocabularies
Sabine Deligne, Ellen Eide, et al.
INTERSPEECH - Eurospeech 2001
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 SPARCLEsystem, 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 performanceevaluation results and contrast our approach with other relevant access control and privacy policy frameworks such as P3P, EPAL, and XACML. © 2010 ACM.
Sabine Deligne, Ellen Eide, et al.
INTERSPEECH - Eurospeech 2001
Ziyang Liu, Sivaramakrishnan Natarajan, et al.
VLDB
Charles H. Bennett, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory
Hendrik F. Hamann
InterPACK 2013