Abstract
Privacy is recognized as one of the key factors regarding the acceptance of ambient intelligence (AmI). However, privacy is neglected in many projects. We address a formal representation of AmI allowing to model systems including privacy expectations and assumptions. In order to be able to compare systems, either existing or theoretically defined, we develop a benchmark framework that is based on this formal representation. We demonstrate the applicability of our approach with a system implementing two different privacy settings.
Keywords
- Differential Privacy
- Ambient Intelligence (AmI)
- Reasoning Cycle
- Situation Description
- Privacy Violations
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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- 1.
Currently, we define only the set of binary relations, due to readability and simplicity. However, this can be changed to any arity of relation without influence on the remaining representation specification.
- 2.
In general, usage of \(\diamond [t_i,t_j]\) is possible, but would lead to multiple interpretations of a single knowledge base.
- 3.
In [15] data is collected at three different locations in the reasoning cycle. In general, we assume subsequent adaption of existing systems unfeasible.
- 4.
We randomly decided to use this duration and also assume a maximal duration of 1000 milliseconds between reasoning cycles.
- 5.
We applied a computer featuring an Intel Core i7-2600 CPU and 16 GB memory.
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Acknowledgement
We acknowledge German Research Foundation (DFG) funding for project SOCIAL (FR 806/15-1). We thank the four anonymous reviewers for their thoughtful and constructive comments.
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van de Ven, J., Dylla, F. (2015). Knowledge vs. Support. In: De Ruyter, B., Kameas, A., Chatzimisios, P., Mavrommati, I. (eds) Ambient Intelligence. AmI 2015. Lecture Notes in Computer Science(), vol 9425. Springer, Cham. https://doi.org/10.1007/978-3-319-26005-1_7
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DOI: https://doi.org/10.1007/978-3-319-26005-1_7
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