TY - GEN
T1 - A fault-tolerant and efficient scheme for data aggregation over groups in the smart grid
AU - Knirsch, F.
AU - Engel, D.
AU - Erkin, Z.
N1 - Conference code: 134376
Cited By :9
Export Date: 14 December 2023
Correspondence Address: Knirsch, F.; Josef Ressel Center for User-Centric Smart Grid Privacy, Urstein Sued 1, Austria; email: [email protected]
Funding details: Bundesministerium für Wissenschaft und Forschung, BMWF
Funding details: Salzburger Landesregierung
Funding text 1: ACKNOWLEDGMENT The financial support by the Austrian Federal Ministry of Science, Research and Economy, the Austrian National Foundation for Research, Technology and Development and the Federal State of Salzburg is gratefully acknowledged.
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PY - 2017
Y1 - 2017
N2 - Aggregating data in the smart grid is an important issue for obtaining the total consumption of a group of households. In order to aggregate data in a privacy preserving manner, it has to be assured that individual contributions are untraceable and only the sum is visible to an aggregator. For billing, network security and statistical analysis data from different types of customers (e.g., industrial, residential) has to be aggregated separately. This paper presents a fault-tolerant and efficient scheme for aggregating data over different groups while preserving the privacy of the households. We propose to build on the Chinese Remainder Theorem for aggregating over groups and on a fault-tolerant and tree-based approach for increasing efficiency. The resulting protocol is evaluated in terms of privacy, complexity and real-world applicability, such as dynamic joins and leaves. © 2017 IEEE.
AB - Aggregating data in the smart grid is an important issue for obtaining the total consumption of a group of households. In order to aggregate data in a privacy preserving manner, it has to be assured that individual contributions are untraceable and only the sum is visible to an aggregator. For billing, network security and statistical analysis data from different types of customers (e.g., industrial, residential) has to be aggregated separately. This paper presents a fault-tolerant and efficient scheme for aggregating data over different groups while preserving the privacy of the households. We propose to build on the Chinese Remainder Theorem for aggregating over groups and on a fault-tolerant and tree-based approach for increasing efficiency. The resulting protocol is evaluated in terms of privacy, complexity and real-world applicability, such as dynamic joins and leaves. © 2017 IEEE.
KW - Data privacy
KW - Electric power transmission networks
KW - Fault tolerance
KW - Smart power grids
KW - Aggregate datum
KW - Chinese remainder theorem
KW - Data aggregation
KW - Efficient schemes
KW - Fault-tolerant
KW - Privacy preserving
KW - Real-world
KW - Tree-based approach
KW - Network security
U2 - 10.1109/WIFS.2017.8267646
DO - 10.1109/WIFS.2017.8267646
M3 - Conference contribution
SN - 978-1-5090-6770-1
SP - 1
EP - 6
BT - 2017 IEEE Workshop on Information Forensics and Security (WIFS)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Workshop on Information Forensics and Security, WIFS 2017
Y2 - 4 December 2017 through 7 December 2017
ER -
SDG 7 Affordable and Clean Energy