Secure end-to-end processing of smart metering data

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

  • Andrey Brito, Universidade Federal de Campina Grande, Brasilien
  • Christof Fetzer, TU Dresden, Tyskland
  • Stefan Köpsell, TU Dresden, Tyskland
  • Peter Pietzuch, Imperial College, London, Storbritannien
  • Marcelo Pasin, Université de Neuchâtel, Schweiz
  • Pascal Felber, Université de Neuchâtel, Schweiz
  • Keiko Fonseca, Universidade Tecnologica Federal do Parana, Brasilien
  • Marcelo Rosa, Universidade Tecnologica Federal do Parana, Brasilien
  • Luiz Gomes-Jr, Universidade Tecnologica Federal do Parana, Brasilien
  • Rodrigo Riella, LACTEC, Brasilien
  • Charles Prado, INMETRO, Brasilien
  • Luiz F. Rust, INMETRO
  • ,
  • Daniel Enrique Lucani Rötter
  • Marton Sipos, Chocolate Cloud ApS
  • ,
  • Laszlo Nagy, Chocolate Cloud ApS
  • ,
  • Marcell Fehér
Cloud computing considerably reduces the costs of deploying applications through on-demand, automated and fine-granular allocation of resources. Even in private settings, cloud computing platforms enable agile and self-service management, which means that physical resources are shared more efficiently. Nevertheless, using shared infrastructures also creates more opportunities for attacks and data breaches. In this paper, we describe the SecureCloud approach. The SecureCloud project aims to enable confidentiality and integrity of data and applications running in potentially untrusted cloud environments. The project leverages technologies such as Intel SGX, OpenStack and Kubernetes to provide a cloud platform that supports secure applications. In addition, the project provides tools that help generating cloud-native, secure applications and services that can be deployed on potentially untrusted clouds. The results have been validated in a real-world smart grid scenario to enable a data workflow that is protected end-to-end: from the collection of data to the generation of high-level information such as fraud alerts.
OriginalsprogEngelsk
Artikelnummer19
Tidsskrift Journal of Cloud Computing
Vol/bind8
ISSN2192-113X
DOI
StatusUdgivet - dec. 2019
Eksternt udgivetJa

Se relationer på Aarhus Universitet Citationsformater

Projekter

ID: 170669647