Provably privacy-preserving distributed data aggregation in smart grids

First published in
Lecture notes in computer science  
Number in series
12122 LNCS
Start Page
153
End Page
173
Citation
IFIP Annual Conference on Data and Applications Security and Privacy (2020)
Contribution to Conference
34th Annual IFIP WG11.3 Conference on Data and Applications Security and Privacy, DBSec 2020  
Publisher DOI
10.1007/978-3-030-49669-2_9
Scopus ID
2-s2.0-85087528241
Publisher
Springer
The digitalization of power systems leads to a significant increase of energy consumers and generators with communication capabilities. Using data of such devices allows for a more efficient grid operation, e.g., by improving the balancing of power demand and supply. Fog Computing is a paradigm that enables efficient aggregation and processing of the measurements provided by energy consumers and generators. However, the introduction of these techniques is hindered by missing trust in the data protection, especially for personal-related data such as electric consumption. To resolve this conflict, we propose a privacy-preserving concept for the hierarchical aggregation of distributed data based on additive secret-sharing. To increase the trust towards the system, we model the concept and provide a formal proof of its confidentiality properties. We discuss the attacker models of colluding and non-colluding adversaries on the data flow and show how our scheme mitigates these attacks.
Subjects
Additive secret sharing
Automated proof
Distributed and decentralized security
Formal model
Smart grid security
Smart metering
DDC Class
004: Informatik