Decoupled Network Functions for Data Privacy
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Solution Overview
Problem
Communication networks face challenges in protecting data privacy, as a limited number of network entities collect and control operation data, raising concerns about data protection and privacy, especially regarding identification and lifestyle information of data source providers and entities.
Innovation Solution
A system with separately controlled network functions for data collection, privatization, analysis, and distribution, where each function is operated by a different provider, ensuring decoupling and distributing ownership among multiple providers, and utilizing artificial intelligence for data analysis, to enhance data privacy and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a limited number of network entities collect and control operation data, then data collection and control efficiency is improved, but data privacy and security deteriorate
Solution Approach 1:
The patent segments the data collection and control functions into multiple independent network entities. Instead of one centralized entity controlling all data, the system divides data collection, data storage, data analysis, and data distribution among separate entities. This segmentation prevents any single entity from having full access to all data, thereby protecting privacy while maintaining operational efficiency through specialized functions.
Solution Approach 2:
The patent introduces intermediary entities that act as mediators between data sources and data users. These intermediaries process and anonymize data before transmission, ensuring that neither the original data sources nor the end users can trace data back to individual entities. This intermediary layer preserves privacy while enabling useful data analysis and control functions.
2Ease of operation
If one network entity performs all data operations, then operational simplicity is improved, but data control and privacy protection deteriorate
Solution Approach 1:
The patent divides data operations into distinct segments performed by different network entities: data collection by first entities, data anonymization by second entities, data analysis by third entities, and result distribution by fourth entities. This segmentation enhances security through distributed control while maintaining operational simplicity through standardized interfaces and protocols between entities.
Solution Approach 2:
Each network entity in the patent is assigned specific functional qualities appropriate to its role. Data collection entities have capabilities optimized for gathering information, anonymization entities specialize in privacy protection techniques, analysis entities focus on data processing, and distribution entities handle result delivery. This local specialization improves both security and operational efficiency.
3Productivity
If data is centralized for analysis, then analysis efficiency is improved, but privacy protection deteriorates
Solution Approach 1:
The patent applies preliminary anonymization processing to data before it is transmitted to analysis entities. By removing personally identifiable information and sensitive details in advance, the system enables efficient centralized analysis while preventing privacy breaches. The anonymization step prepares data for analysis in a way that preserves utility while eliminating privacy risks.
Solution Approach 2:
The patent extracts and removes sensitive personal information from data sets before analysis. By taking out identifiable elements such as names, addresses, and unique identifiers, the system retains the analytical value of the data while eliminating privacy concerns. This extraction process allows efficient centralized analysis without compromising individual privacy.
Data Source
AI summary
Methods and systems for data management in communication networks. An aspect provides a system including a first network function and a second network functions. The first network function is configured for collecting data and storing the collected data. The second network function is configured for removing private information from the collected data and producing privatized data. The first and the second network functions are separately controlled and operated by different providers. The first network function is operated by a first provider via a first controller. The second network function is operated by a second provider via a second controller. The separately controlled feature of such a network architecture enhances data privacy by ensuring different entities control the collection of data and the privatization of the collected data.