Effectiveness of Privacy Techniques in Smart Metering Systems

Conference · Wed Jun 01 00:00:00 EDT 2022

DOI:https://doi.org/10.1109/CSCI54926.2021.00177· OSTI ID:1875363

Peralta-Peterson, Martin ^[1]; Kotevska, Olivera  ^[2]

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1. University of California, San Diego
2. ORNL

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.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1875363
• Resource Relation: Conference: 8th International Conference on Computational Science and Computational Intelligence (CSCI'21) - Las Vegas/Virtual, Nevada, United States of America - 12/15/2021 10:00:00 AM-12/17/2021 10:00:00 AM
• Country of Publication: United States
• Language: English