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This paper describes a tool that may be used to create and analyse privacy policies based on the InfoPriv model (proposed by us elsewhere). It is called the Privacy Workbench and consists of four modules: the Privacy Policy, Graph Module, Inference Engine and Rule Base. The Workbench maps privacy policies to graphs called information can-flow graphs. The vertices of an information can-flow graph represent entities while the arcs depict the potential information flow: It is the purpose of the Inference Engine to analyse the graph for all possible information flow between entities including conflicting information flow. It does this by using graph-traversal algorithms. The Inference Engine further resolves conflicting information flows. It uses a rule-based approach to choose the "best" arcs to remove in order to resolve conflicts. These rules are contained in the Rule-base and make use of the information can-flow graph's structure and specifics of the privacy policy.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |