Health Data Max/Min Aggregation with Paillier Homomorphic Encryption
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Solution Overview
Problem
Existing privacy protection data aggregation schemes in medical IoT cannot provide non-additive statistics such as max/min and median, limiting the ability to monitor user health data effectively.
Innovation Solution
A data max/min aggregation method and system using a Paillier cryptosystem for encrypting health data, enabling a fog node to determine max/min reports and a control center to decrypt and aggregate these values while ensuring privacy, utilizing the homomorphic property of the Paillier cryptosystem.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing privacy protection data aggregation schemes are used, then user privacy is protected, but non-additive aggregation statistics (such as max/min and median) cannot be provided
Solution Approach 1:
The patent introduces a fog node as an intermediary between the client and control center. The fog node receives encrypted health data reports from clients, performs homomorphic multiplication to aggregate data while preserving encryption, and forwards results to the control center. This intermediary enables non-additive aggregation (max/min) without compromising privacy, as the fog node operates on encrypted data and the control center only receives final aggregated results
Solution Approach 2:
The patent changes the mathematical operation from additive aggregation to multiplicative aggregation in the homomorphic domain. By using homomorphic multiplication of encrypted values, the system can recover max/min statistics through decryption of the product, whereas traditional additive schemes only yield sum/average. This parameter change in the aggregation operation enables non-additive statistics while maintaining encryption throughout the process
2Reliability
If health data reports are encrypted using Paillier cryptosystem, then privacy is protected, but the fog node cannot directly compare values to determine max/min
Solution Approach 1:
Instead of trying to compare encrypted values directly (which is computationally hard), the patent inverts the approach: the fog node performs homomorphic multiplication of all encrypted health data reports, then the control center decrypts the product. The decrypted result contains information about max/min values that can be extracted through mathematical analysis, avoiding the need for direct comparison of encrypted values
Solution Approach 2:
The patent replaces the mechanical comparison operation (which requires plaintext) with homomorphic multiplication in the cryptographic domain. This substitution allows the fog node to process encrypted data without decryption, maintaining privacy while enabling statistical aggregation through algebraic operations rather than direct value comparison
Data Source
AI summary
The present disclosure provides a data maximum/minimum value (max/min) aggregation method and system for privacy protection. A Paillier cryptosystem is used to encrypt user data, so as to protect privacy and security of user health data. Further, time aggregation is implemented to help a control center obtain an overall health condition of a client in one aggregation period. By using a homomorphic property of the Paillier cryptosystem, the present disclosure implements aggregation of a max/min of privacy protection, and helps the control center obtain a max or a min of health data of the client in the aggregation period.