Sensing Network Privacy Protection for 5G Communication Requests
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Solution Overview
Problem
There is an urgent need to ensure user privacy protection in 5G-advanced communication networks that support sensing functions, particularly in scenarios involving autonomous driving, assisted driving, unmanned aerial vehicles, and smart cities, where sensitive user data may be exposed.
Innovation Solution
A communication method is implemented by sensing function network elements to receive requests, perform security protection processing on user data, and send secured sensing results to prevent data leakage, utilizing information from request messages to determine the need for security processing based on requester, service type, area, accuracy, and purpose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sensing data including user data is directly provided to another network element, then sensing service efficiency is improved, but user privacy security deteriorates
Solution Approach 1:
The patent extracts sensitive user data from the original sensing data through security protection processing. The sensing function network element identifies and separates personal identifiable information from sensing results, applying differential privacy techniques to remove or mask sensitive attributes while preserving useful sensing information for service delivery.
Solution Approach 2:
The patent introduces a security protection processing mechanism as an intermediary between data collection and data sharing. This intermediary layer applies differential privacy algorithms and security policies to transform raw sensing data into protected sensing results, enabling safe data exchange without direct exposure of user privacy.
2Object-affected harmful factors
If security protection processing is performed on user data, then user privacy security is improved, but processing complexity increases
Solution Approach 1:
The patent implements preliminary action by establishing security protection policies and differential privacy parameters in advance. The sensing function network element pre-configures privacy budget allocation, sensitivity parameters, and protection rules before processing sensing data, reducing real-time processing complexity while maintaining security standards.
Solution Approach 2:
The patent applies parameter changes through differential privacy techniques, where privacy protection strength and noise addition levels are adjusted based on data sensitivity and service requirements. By dynamically modifying processing parameters rather than using fixed complex algorithms, the system achieves effective privacy protection with manageable complexity.
3Loss of information
If differential privacy protection is applied to sensing data, then data utility is maintained, but measurement precision of user information deteriorates
Solution Approach 1:
The patent applies local quality by implementing differential privacy protection at specific sensitive data points rather than uniformly across all sensing data. The sensing function network element identifies which fields require protection (e.g., location, identity) and applies privacy-preserving transformations only to those locations, maintaining high precision in non-sensitive areas while protecting privacy where needed.
Data Source
AI summary
A communication method. A sensing function network element receives a first request message for requesting to obtain a sensing result, where the sensing result is obtained by processing sensing data. The sensing function network element obtains the sensing data that includes data of a first user. The sensing function network element performs security protection processing on the data of the first user to obtain a sensing result, and feeds back the sensing result. After the sensing function network element receives the first request message for requesting to obtain the sensing result, in response to the obtained sensing data including user data, the sensing function network element performs security protection processing on the user data to obtain the sensing result, and feeds back the sensing result, to avoid leakage of user privacy caused by directly providing the obtained user data to other network elements.