Homomorphic Encryption for Smart Meter Data Privacy
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Solution Overview
Problem
Smart metering systems face significant privacy risks due to the transmission of sensitive data, such as utility consumption values, which can include socio-economic and demographic information.
Innovation Solution
The method involves encrypting data values using fully homomorphic encryption with a secret key, aggregating the encrypted data, and transmitting the aggregated values to a remotely located using entity, which can then decrypt the data for further processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data values are transmitted in plaintext for efficient processing, then processing efficiency is improved, but privacy protection deteriorates
Solution Approach 1:
The patent applies preliminary action by encrypting data values before transmission and aggregation. The encryption operation is performed in advance at the collecting stations, so that subsequent aggregation and processing can be done on encrypted data without decryption, thus maintaining both efficiency and privacy protection throughout the data lifecycle.
Solution Approach 2:
The patent introduces encryption as an intermediary mechanism between data collection and data processing. The fully homomorphic encryption scheme acts as a mediator that allows the using entity to process aggregated data without ever accessing the plaintext, thus resolving the conflict between processing efficiency and privacy protection.
2Object-affected harmful factors
If encryption is applied to protect privacy, then privacy protection is improved, but computational complexity increases
Solution Approach 1:
The patent segments the encryption operations across multiple collecting stations, where each station independently encrypts its own data values. This segmentation distributes the computational burden and avoids concentrating all encryption complexity in a single entity, making the overall system more manageable despite the inherent complexity of fully homomorphic encryption.
3Object-affected harmful factors
If data aggregation is performed on encrypted values, then privacy protection is maintained, but aggregation capability is limited
Solution Approach 1:
The patent changes the parameter space by using fully homomorphic encryption, which allows arithmetic operations (including aggregation) to be performed directly on encrypted data. This parameter change enables the system to maintain privacy protection while preserving aggregation capability, as the encryption scheme is specifically designed to support these operations in the encrypted domain.
Data Source
AI summary
A method comprising encrypting data values by a fully homomorphic encryption using a secret key to obtain encrypted data values, aggregating encrypted remote data in an encrypted aggregated value by performing a sum of the respective encrypted data values, performing one or more functions on the basis of the set of data values at the using entity, supplying the encrypted aggregated value to the using entity, which is configured to receive the secret key from a separated entity, decrypting the encrypted aggregated value using the secret key to obtain a decrypted sum of data values, performing data-related functions on the basis of the decrypted sum of the respective data values at the using entity.