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Local Differential Privacy for Smart Meter Data Sharing. (arXiv:2311.04544v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Energy disaggregation techniques, which use smart meter data to infer
appliance energy usage, can provide consumers and energy companies valuable
insights into energy management. However, these techniques also present privacy
risks, such as the potential for behavioral profiling. Local differential
privacy (LDP) methods provide strong privacy guarantees with high efficiency in
addressing privacy concerns. However, existing LDP methods focus on protecting
aggregated energy consumption data rather than individual appliances.
Furthermore, these methods do not consider the fact that smart meter …
companies consumers data data sharing differential privacy efficiency energy energy management high insights local management privacy privacy risks profiling risks sharing smart smart meter techniques