Abstract
The energy industry has recently begun using smart meters to take fine-grained readings of energy usage. These smart meters enable flexible time-of-use billing, forecasting, and demand response, but they also raise serious user privacy concerns. We propose a novel technique for provably hiding sensitive power consumption information in the overall power consumption stream. Our technique relies on a rechargeable battery that is connected to the household’s power supply. This battery is used to modify the household’s power consumption by adding or subtracting noise (i.e., increasing or decreasing power consumption), in order to establish strong privacy guarantees in the sense of differential privacy. To achieve these privacy guarantees in realistic settings, we first investigate the influence of, and the interplay between, capacity and throughput bounds that batteries face in reality. We then propose an integrated method based on noise cascading that allows for recharging the battery on-the-fly so that differential privacy is retained, while adhering to capacity and throughput constraints, and while keeping the additional consumption of energy induced by our technique to a minimum.
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Notes
- 1.
We stress that we wish to avoid wasting any energy in general. Our solution discards only the small amount of energy that arises for generating the noise of the battery recharging process.
- 2.
Selling electricity would be an alternative. However, an accurate treatment would additionally require a detailed cost model; moreover selling electricity after drawing it from the provider is typically not economical. We thus do not further consider this case.
- 3.
In practice, the amount of energy that a battery can provide usually is slightly smaller when under heavy load; we ignore this here.
- 4.
For this work we only consider Laplacian noise. Applying other, e.g., already bounded noise distributions or other masking techniques is considered future work.
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Backes, M., Meiser, S. (2014). Differentially Private Smart Metering with Battery Recharging. In: Garcia-Alfaro, J., Lioudakis, G., Cuppens-Boulahia, N., Foley, S., Fitzgerald, W. (eds) Data Privacy Management and Autonomous Spontaneous Security. DPM SETOP 2013 2013. Lecture Notes in Computer Science(), vol 8247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54568-9_13
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