TY - GEN
T1 - Privacy Assessment of Data Flow Graphs for an Advanced Recommender System in the Smart Grid
AU - Knirsch, F.
AU - Engel, D.
AU - Neureiter, C.
AU - Frincu, M.
AU - Prasanna, V.
N1 - Conference code: 160439
Cited By :5
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: Marshallplan-Jubiläumsstiftung
Funding details: Austrian Federal Ministry of Economy, Family and Youth, BMWFJ
Funding details: U.S. Department of Energy, USDOE, DE-OE0000192
Funding text 1: The financial support of the Josef Ressel Center by the Austrian Federal Ministry of Economy, Family and Youth and the Austrian National Foundation for Research, Technology and Development is gratefully acknowledged. Funding by the Austrian Marshall Plan Foundation is gratefully acknowledged. The authors would like to thank Norbert Egger for his contribution to the prototypical implementation. Funding by the Federal State of Salzburg is gratefully acknowledged.
Funding text 2: This material is based upon work supported by the United States Department of Energy under Award Number number DE-OE0000192, and the Los Angeles Department of Water and Power (LA DWP). The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, the LA DWP, nor any of their employees.
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PY - 2015
Y1 - 2015
N2 - The smart grid paves the way to a number of novel applications that benefit a variety of stakeholders including network operators, utilities and customers as well as third party developers such as electric vehicle manufacturers. In order to roll out an integrated and connected grid that combines energy and information flows and that fosters bidirectional communications, data and information needs to be exchanged and aggregated. However, collecting, transmitting and combining information from different sources has some severe privacy impacts on customers. Furthermore, customer acceptance and participation is the key to many smart grid applications such as demand response. In this paper we present (i) an approach for the model-based assessment of privacy in the smart grid that draws on a formal use case description (data flow graphs) and allows to asses the privacy impact of such use cases at early design time; and (ii) based on that assessment we introduce a recommender system for smart grid applications that allows users and vendors to make informed decisions on the deployment, use and active participation in smart grid use cases with respect to their individual privacy. © Springer International Publishing Switzerland 2015.
AB - The smart grid paves the way to a number of novel applications that benefit a variety of stakeholders including network operators, utilities and customers as well as third party developers such as electric vehicle manufacturers. In order to roll out an integrated and connected grid that combines energy and information flows and that fosters bidirectional communications, data and information needs to be exchanged and aggregated. However, collecting, transmitting and combining information from different sources has some severe privacy impacts on customers. Furthermore, customer acceptance and participation is the key to many smart grid applications such as demand response. In this paper we present (i) an approach for the model-based assessment of privacy in the smart grid that draws on a formal use case description (data flow graphs) and allows to asses the privacy impact of such use cases at early design time; and (ii) based on that assessment we introduce a recommender system for smart grid applications that allows users and vendors to make informed decisions on the deployment, use and active participation in smart grid use cases with respect to their individual privacy. © Springer International Publishing Switzerland 2015.
KW - Automobile manufacture
KW - Crashworthiness
KW - Data flow analysis
KW - Data flow graphs
KW - Data privacy
KW - Data transfer
KW - Electric power transmission networks
KW - Flow graphs
KW - Graphic methods
KW - Information systems
KW - Recommender systems
KW - Sales
KW - Bi-directional communication
KW - Customer acceptance
KW - Data and information
KW - Energy and information
KW - Individual privacy
KW - Novel applications
KW - Smart grid applications
KW - Vehicle manufacturers
KW - Smart power grids
U2 - 10.1007/978-3-319-27668-7_6
DO - 10.1007/978-3-319-27668-7_6
M3 - Conference contribution
SN - 978-3-319-27667-0
VL - 576
BT - Information Systems Security and Privacy
PB - Springer International Publishing
T2 - 1st International Conference on Information Systems Security and Privacy, ICISSP 2015
Y2 - 9 February 2015 through 11 February 2015
ER -
SDG 7 Affordable and Clean Energy