Data Analysis System with Stream and Block Cipher Encryption
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Institutions face privacy risks when sharing user data with external analysis companies, as existing data analysis technologies do not adequately protect personal information during analysis processes.
Innovation Solution
A data analysis system and method utilizing a combination of stream and block cipher algorithms to encrypt raw data and analysis results, ensuring secure data transmission and maintaining flexibility in data analysis by calculating attribute-value correspondences for secure data exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If raw data is provided to external analysis companies for analysis, then data analysis capability is improved, but data security and privacy protection deteriorate
Solution Approach 1:
The patent applies preliminary action by encrypting the raw data before it is transmitted to the external analysis company. The encryption is performed in advance on the data provider's side, so that when the data reaches the analysis company, it is already in an encrypted state. This preliminary encryption action ensures that the data analysis can proceed while the sensitive information remains protected throughout the analysis process.
Solution Approach 2:
The patent introduces encryption as an intermediary mechanism between the data provider and the analysis company. The encrypted data acts as a mediator that allows the analysis company to perform statistical operations without directly accessing the plaintext sensitive information. This intermediary encryption layer enables the analysis function while blocking the privacy leakage path.
2Object-affected harmful factors
If data is encrypted before analysis, then data security is improved, but analysis complexity increases
Solution Approach 1:
The patent applies parameter changes by transforming the data from plaintext to ciphertext form before analysis. This parameter transformation (encryption) changes the state of the data while preserving its statistical properties, allowing standard SQL operations to work on encrypted data. The encryption parameters are managed through automatic key generation and management, which reduces the operational complexity despite the cryptographic transformations.
3Object-affected harmful factors
If encryption algorithms are applied to raw data, then privacy protection is improved, but processing efficiency decreases
Solution Approach 1:
The patent extracts only the necessary statistical information from the encrypted data without requiring decryption. By using homomorphic encryption properties, the system extracts statistical features (such as counts, sums, averages) directly from the ciphertext, avoiding the need to process the full encrypted dataset through computationally intensive decryption operations. This extraction approach maintains privacy protection while improving processing efficiency.
Data Source
AI summary
The application discloses a data analysis system and a data analysis method. The data analysis system includes a data provider host and a data analysis host. The data provider host is configured to perform a stream cipher algorithm based on raw data to obtain first data. The data analysis host is configured to perform a data analysis based on the first data to obtain an analysis result. The data provider host or the data analysis host is further configured to perform a block cipher algorithm based on the analysis result to obtain second data, and send the second data to an external device. The data provider host is further configured to calculate an attribute-value correspondence between the raw data and the second data, and send the attribute-value correspondence to the external device.