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Engineering Adaptive Privacy

As mobile computing applications have become commonplace, it is increasingly important for them to address end-users' privacy requirements. Mobile privacy requirements depend on a number of contextual socio-cultural factors to which mobility adds another level of contextual variation. However, traditional requirements elicitation methods do not sufficiently account for contextual factors and therefore cannot be used effectively to represent and analyse the privacy requirements of mobile end users. On the other hand, methods that investigate contextual factors tend to produce data that does not lend itself to the process of requirements extraction. To address this problem we have developed a Privacy Requirements Distillation approach that employs a problem analysis model to extract and refine privacy requirements for mobile applications from raw data gathered through empirical studies involving end users. We demonstrate our approach using qualitative data from an empirical study of a mobile social networking application.