Abstract
The continuing advancements in microprocessor technologies are putting more and more computing power into small devices. Today smartphones are especially popular. Nevertheless, for resource intensive tasks such devices are still too constrained. However, the simultaneous trend of providing computing resources as a commodity on a pay-as-you-go basis (cloud computing) combined with such mobile devices facilitates interesting applications: Mobile clients can simply outsource resource intensive tasks to the cloud. Since clients have to pay a cloud provider (CP) for consumed resources, e.g. instance hours of virtual machines, clients may consider it as privacy intrusive that the CP is able to record the activity pattern of users, i.e. how often and how much resources are consumed by a specific client. In this paper we present a solution to this dilemma which allows clients to anonymously consume resources of a CP such that the CP is not able to track users’ activity patterns. We present a scenario which integrates up-to-date security enhanced platforms as processing nodes and a recent cloud payment scheme together with a concrete implementation supporting the practicality of the proposed approach.
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Pirker, M., Slamanig, D., Winter, J. (2012). Practical Privacy Preserving Cloud Resource-Payment for Constrained Clients. In: Fischer-Hübner, S., Wright, M. (eds) Privacy Enhancing Technologies. PETS 2012. Lecture Notes in Computer Science, vol 7384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31680-7_11
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DOI: https://doi.org/10.1007/978-3-642-31680-7_11
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