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Context-aware mobile security

Experimental validation of reliable and secure context detection
: Jung, Christian; Feth, Denis

Kaiserslautern, 2016, 15 pp.
IESE-Report, 019.16/E
Reportnr.: 019.16/E
Fraunhofer IESE ()
context awareness; context modeling; security

The exploitation of context-awareness, especially in mobile devices bears a huge potential. For example, mobile workers benefit from systems that adapt security settings or user interfaces to the current situation. However, the correct detection of contexts strongly relies on raw data from various context information sources that might be neither trustworthy nor authoritative. In this work, we present an extension to a context model that explicitly copes with trustworthiness of context information, i.e., its vulnerability to forgery, as well as their conduciveness denoting the source's decisive impact on context detection. Context descriptions based on this model can, for example, be used in security-critical environments to enforce security policies. We show the applicability of our approach in an industrial setting. In addition, we present the results of our experiments with respect to precision and recall of the context detection.