Smart Meter Data Anonymization via Convergence Thresholds
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Solution Overview
Problem
Smart metering data privacy is compromised due to the detailed energy usage information collected, which can reveal personal activities and habits, posing a significant threat to users' privacy, especially as smart grids integrate advanced metering infrastructure and two-way communication networks, necessitating effective anonymization methods.
Innovation Solution
A device and method that modify consumption data by introducing a processor to generate modified consumption data based on obtained data, using rules and convergence factors to ensure deviations from original data do not exceed predetermined thresholds, thereby anonymizing the information while maintaining operational accuracy for utility providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If smart meters collect detailed energy usage information, then operational accuracy for utility providers is improved, but user privacy is compromised
Solution Approach 1:
The patent introduces an anonymization device as an intermediary component between the smart meter and the utility provider's data system. This device processes the detailed consumption data through anonymization algorithms that remove personally identifiable information while preserving energy usage patterns needed for billing and grid management, thus mediating between privacy protection and operational accuracy requirements
Solution Approach 2:
The patent extracts and removes personally identifiable information from the detailed consumption data while retaining the energy usage patterns. The anonymization process separates the identifiable elements from the operational data, allowing utility providers to access energy consumption information without accessing user identity or specific behavioral patterns
2Object-affected harmful factors
If consumption data is anonymized to protect privacy, then user privacy is improved, but data reliability for utility operations may deteriorate
Solution Approach 1:
The patent applies parameter changes to the consumption data by transforming it through anonymization algorithms that modify data representation while preserving essential characteristics. The system adjusts data parameters such as time granularity and aggregation levels to maintain reliability for utility operations while protecting privacy through controlled transformation
3Productivity
If detailed metering data is collected and analyzed, then operational functionality is improved, but privacy threats increase
Solution Approach 1:
The patent implements preliminary anonymization action on consumption data before it is transmitted to or stored by utility providers. By performing the anonymization process in advance, the system ensures that detailed operational data is made available for productivity-enhancing analysis while the privacy-protecting transformation is already applied, preventing exposure of sensitive information
Data Source
AI summary
A device comprising an input for obtaining consumption data relating to the consumption of a utility provided by a utility provider, an output for outputting modified consumption data and a processor arranged to generate the modified consumption data based on obtained consumption data so that the modified consumption data starts to converge with the obtained consumption data if a deviation of the obtained consumption data from the modified consumption data exceeds a predetermined threshold.