Abstract
Smart grid technologies enable timely energy billing for residential homes. The ability to react to energy demands during peak hours allows energy providers to conserve power and operate efficiently. However, these data streams are also susceptible to privacy attacks within the energy company and from outside hackers. We implemented four different privacy models: k-anonymous, l-diversity, t-closeness, and ϵ-differential privacy. We demonstrate the models' effectiveness using a real-world dataset composed of 15 different residential households with energy consumption data spanning over a year.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 675-678 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781665458412 |
| DOIs | |
| State | Published - 2021 |
| Event | 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021 - Las Vegas, United States Duration: Dec 15 2021 → Dec 17 2021 |
Publication series
| Name | Proceedings - 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021 |
|---|
Conference
| Conference | 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021 |
|---|---|
| Country/Territory | United States |
| City | Las Vegas |
| Period | 12/15/21 → 12/17/21 |
Funding
This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle,LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725.
Keywords
- differential privacy
- k-anonymity
- l-diversity
- smart meter
- t-closeness