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PrivAgE: A Toolchain for Privacy-Preserving Distributed Aggregation on Edge-Devices

dc.contributor.authorLiebenow, Johannes
dc.contributor.authorImort, Timothy
dc.contributor.authorFuchs, Yannick
dc.contributor.authorHeisel, Marcel
dc.contributor.authorKäding, Nadja
dc.contributor.authorRupp, Jan
dc.contributor.authorMohammadi, Esfandiar
dc.date2024-11-01
dc.date.accessioned2025-01-13T11:15:16Z
dc.date.available2025-01-13T11:15:16Z
dc.date.issued2024
dc.description.abstractValuable insights, such as frequently visited environments in the wake of the COVID-19 pandemic, can oftentimes only be gained by analyzing sensitive data spread across edge-devices like smartphones. To facilitate such an analysis, we present a toolchain called PrivAgE for a distributed, privacy-preserving aggregation of local data by taking the limited resources of edge-devices into account. The distributed aggregation is based on secure summation and simultaneously satisfies the notion of differential privacy. In this way, other parties can neither learn the sensitive data of single clients nor a single client’s influence on the final result. We perform an evaluation of the power consumption, the running time and the bandwidth overhead on real as well as simulated devices and demonstrate the flexibility of our toolchain by presenting an extension of the summation of histograms to distributed clustering.de
dc.identifier.doi10.1007/s13218-023-00823-8
dc.identifier.issn1610-1987
dc.identifier.urihttp://dx.doi.org/10.1007/s13218-023-00823-8
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45576
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 38, No. 3
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectAcoustic Scene Classification (ASC)
dc.subjectClustering
dc.subjectDifferential Privacy
dc.subjectDistributed and Secure Aggregation
dc.subjectEdge-Devices
dc.titlePrivAgE: A Toolchain for Privacy-Preserving Distributed Aggregation on Edge-Devicesde
dc.typeText/Journal Article
mci.reference.pages183-188

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