| Title | Privacy Preservation of Aggregated Data Using Virtual Battery in the Smart Grid |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Kserawi, Fawaz, Malluhi, Qutaibah M. |
| Conference Name | 2020 IEEE 6th International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application (DependSys) |
| Keywords | Batteries, Collaboration, composability, Data analysis, Data models, Differential privacy, Encryption, Human Behavior, Metrics, Perturbation methods, Policy-Governed Secure Collaboration, privacy, pubcrawl, resilience, Resiliency, Scalability, Smart grid, smart grid consumer privacy, Smart grids, Smart Metering |
| Abstract | Smart Meters (SM) are IoT end devices used to collect user utility consumption with limited processing power on the edge of the smart grid (SG). While SMs have great applications in providing data analysis to the utility provider and consumers, private user information can be inferred from SMs readings. For preserving user privacy, a number of methods were developed that use perturbation by adding noise to alter user load and hide consumer data. Most methods limit the amount of perturbation noise using differential privacy to preserve the benefits of data analysis. However, additive noise perturbation may have an undesirable effect on billing. Additionally, users may desire to select complete privacy without giving consent to having their data analyzed. We present a virtual battery model that uses perturbation with additive noise obtained from a virtual chargeable battery. The level of noise can be set to make user data differentially private preserving statistics or break differential privacy discarding the benefits of data analysis for more privacy. Our model uses fog aggregation with authentication and encryption that employs lightweight cryptographic primitives. We use Diffie-Hellman key exchange for symmetrical encryption of transferred data and a two-way challenge-response method for authentication. |
| DOI | 10.1109/DependSys51298.2020.00024 |
| Citation Key | kserawi_privacy_2020 |
Privacy Preservation of Aggregated Data Using Virtual Battery in the Smart Grid