Framework Integrating Lossy Compression and Perturbation for the Case of Smart Meter Privacy

• DOI: 10.3390/electronics9030465
• Publication Date: 2020-03-10T15:59:36Z
• Authors: Maik Plenz; Chaoyu Dong; Florian Grumm; Marc Florian Meyer; Marc Schumann; Malcom McCulloch; Hongjie Jia; Detlef Schulz
• Keywords: Smart meter; Lossy compression; USable; Homomorphic Encryption

The encoding of high-resolution energy profile datasets from end-users generated by smart electricity meters while maintaining the fidelity relevant information seems to be one backbones electrical markets. In end-user sphere grids, specific load curves households can easily utilized aggregate detailed about customer’s daily activities, which would attractive for cyber attacks. Based on a dataset measured meter installed in German household, this paper integrates two complementary approaches encrypt datasets. On hand, explains an integration lossy compression and classification technique, is usable individual consumption profiles households. other perturbation approach with Gaussian distribution used enhance safety large amount privacy profiles. By complete workflow, involving perturbation, developed framework sufficiently cut off chance de-noising attacks private data implement additional, easy-to-handle layer security.