Sanitization models and their limitations

This work explores issues of computational disclosure control. We examine assumptions in the foundations of traditional problem statements and abstract models. We offer a comprehensive framework, based on the notion of an inference game, that unifies various inference problems by parameterizing their problem spaces. This work raises questions regarding the significance of intractability results. We analyze common structural aspects of inference problems via case studies; these emphasize why explicit policies are needed to specify all social context and ethical values relevant to a problem instance. Categories and Subject Descriptors C.2 [Computer-Communication Networks]: General—security and protection; E.m [Data]: Miscellaneous; K.4.1 [Computers and Society]: Public Policy Issues—privacy General Terms Security. Keywords Data sanitization, inference problem, disclosure control, closed world assumption

• Type: Conference
• Year: 2006
• Where: NSPW
• Authors: Rick Crawford, Matt Bishop, Bhume Bhumiratana, Lisa Clark, Karl N. Levitt
• Keywords: Disclosure Control, Distributed And Parallel Computing, Inference Problem, NSPW 2006, Various Inference Problems