Privacy vs. NILM: Obfuscating your Power Consumption with Load Hiding

Load-based load hiding approach

With the development and introduction of smart metering, the energy information from costumers changes from infrequent manual meter readings to fine-grained energy consumption data. On the one hand, these measurements will lead to an improvement in costumers’ energy habits, but on the other hand, the fine-grained data produces information about a household and households’ inhabitants, which give rise to privacy issues because these monitoring results disclose user behavior which could be extracted by smart algorithms and techniques. The loss of privacy by load disaggregation and data mining is a huge upcoming smart grid and social issue which enforces the need for privacy-preserving techniques, which can be divided into the following three possibilities:

1. Anonymization of metering data: The metering data and customer identity are separated by a third-party id
2. Privacy-preserving metering data aggregation: Metering data is geographically encapsulated by aggregating the metering data of co-located consumers 
3. Masking and obfuscation of metering data: Masking the power demand by adding or withdrawing the to the meter visible energy demand with the help of rechargeable batteries or controllable loads.

In the paper

D. Egarter, C. Prokop, and W. Elmenreich. Load hiding of household's power demand. In Proc. IEEE International Conference on Smart Grid Communications (SmartGridComm'14), Venice, Italy, 2014.

a state-of-the-art battery-based load hiding (BLH) technique, which uses a controllable battery to disguise the power consumption and a novel load hiding technique called load-based load hiding (LLH) are presented and compared. A load-based load hiding system controls appliances in a specific way to obfuscate a household’s power demand. For example, an electric water boiler could be instrumented to consume energy in a way that masks the power consumption of smaller household devices like coffee machines or a TV. There is no comfort loss expected for the customer: Overall, the boiler will consume a typical amount of energy and produce the expected amount of hot water.
Using this approach, however, reduces the predictability of your energy consumption, which is good for privacy, but a disadvantage for grid operators.

Impressions from IEEE Conference on Smart Grid Communication 2014

The IEEE Conference on Smart Grid Communication 2014 was held from November the 13th to 14th in Venice. Wilfried Elmenreich, Dominik Egarter and Andrea Monacchi from our group participated at this event.

The conference was organized in 5 different symposia:

• Communications and Networks to enable the Smart Grid
• Cyber Security and Privacy
• Architectures, Control and Operation for Smart Grid, Microgrids and Distributed Resources
• Demand Response and Dynamic Pricing
• Data Management and Grid Analytics

Dominik presented his paper Load Hiding of Household's Power Demand, (Dominik Egarter, Christoph Prokop, Wilfried Elmenreich) in the session on "Cyber Security and Privacy".

Andrea gave a talk about his paper GREEND: An Energy Consumption Dataset of Households in Italy and Austria (Andrea Monacchi, Dominik Egarter, Wilfried Elmenreich, Salvatore D’Alessandro, Andrea M. Tonello) in the "Data Management and Grid Analytics" session.

Load Hiding of Household's Power Demand

Our publication "Load Hiding of Household's Power Demand" is accepted at the IEEE SmartGridComm 2014. The SmartGridComm 2014 will take place in Venice, a fascinating and marvelous Italian city, on November 3-6, 2014.

Load Hiding of Household's Power Demand, Dominik Egarter, Christoph Prokop, Wilfried Elmenreich

With the development and introduction of smart metering, the energy information for costumers will change from infrequent manual meter readings to fine-grained energy consumption data. On the one hand these fine-grained measurements will lead to an improvement in costumers’ energy habits, but on the other hand the fined-grained data produces in- formation about a household and also households’ inhabitants, which are the basis for many future privacy issues. To ensure household privacy and smart meter information owned by the household inhabitants, load hiding techniques were introduced to obfuscate the load demand visible at the household energy meter. In this work, a state-of-the-art battery- based load hiding (BLH) technique, which uses a controllable battery to disguise the power consumption and a novel load hiding technique called load-based load hiding (LLH) are presented. An LLH system uses an controllable household appliance to obfuscate the household’s power demand. We evaluate and compare both load hiding techniques on real household data and show that both techniques can strengthen household privacy but only LLH can increase appliance level privacy.

An authors' version is available in arXiv: http://arxiv.org/abs/1406.2534