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This work discusses several use cases of post-mortem mobile device tracking in which privacy is required e.g. due to client-confidentiality agreements and sensibility of data from government agencies as well as mobile telecommunication providers. We argue that our proposed Bloomfilter based privacy approach is a valuable technical building block for the arising General Data Protection Regulation (GDPR) requirements in this area. In short, we apply a solution based on the Bloom filters data structure that allows a 3rd party to performsome privacy saving setrelations on a mobiletelco’s access logfile or other mobile access logfile from harvesting parties without revealing any other mobile users in the proximity of a mobile base station but still allowing to track perpetrators.
In the area of cloud computing, judging the fulfillment of service-level agreements on a technical level is gaining more and more importance. To support this we introduce privacy preserving set relations as inclusiveness and disjointness based ao Bloom filters. We propose to compose them in a slightly different way by applying a keyed hash function. Besides discussing the correctness of set relations, we analyze how this impacts the privacy of the sets content as well as providing privacy on the sets cardinality. Indeed, our solution proposes to bring another layer of privacy on the sizes. We are in particular interested how the overlapping bits of a Bloom filter impact the privacy level of our approach. We concretely apply our solution to a use case of cloud security audit on access control and present our results with real-world parameters.