Secure end-to-end processing of smart metering data

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Andrey Brito - , Universidade Federal de Campina Grande (Author)
  • Christof Fetzer - , Chair of Systems Engineering, TUD Dresden University of Technology (Author)
  • Stefan Köpsell - , Chair of Privacy and Data Security, TUD Dresden University of Technology (Author)
  • Peter Pietzuch - , Imperial College London (Author)
  • Marcelo Pasin - , University of Neuchatel (Author)
  • Pascal Felber - , University of Neuchatel (Author)
  • Keiko Fonseca - , Universidade Tecnológica Federal do Paraná (Author)
  • Marcelo Rosa - , Universidade Tecnológica Federal do Paraná (Author)
  • Luiz Gomes - , Universidade Tecnológica Federal do Paraná (Author)
  • Rodrigo Riella - , LACTEC (Author)
  • Charles Prado - , Instituto Nacional de Metrologia, Qualidade e Tecnologia (Author)
  • Luiz F. Rust - , Instituto Nacional de Metrologia, Qualidade e Tecnologia (Author)
  • Daniel E. Lucani - , Chocolate Cloud ApS (Author)
  • Márton Sipos - , Chocolate Cloud ApS (Author)
  • László Nagy - , Chocolate Cloud ApS (Author)
  • Marcell Fehér - , Chocolate Cloud ApS (Author)

Abstract

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. 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.

Details

Original languageEnglish
Article number19
JournalJournal of cloud computing
Volume8
Issue number1
Publication statusPublished - 1 Dec 2019
Peer-reviewedYes

External IDs

ORCID /0000-0002-0466-562X/work/142246153

Keywords

Sustainable Development Goals

Keywords

  • Cloud computing, Confidential computing, Privacy, Security, Smart grids, Trusted execution