Privacy Model Masking for 5G Network Service Requests
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Solution Overview
Problem
Existing network services in 5G systems face challenges in effectively protecting privacy-related information, such as UE location, during information exchanges among network actors, especially when user consent is not given for sharing with entities like network operators.
Innovation Solution
A method and system for operating service consumers and providers that allow privacy-related information to be protected by transmitting a privacy indication and receiving a privacy model, enabling the service consumer to process this information securely, using privacy models to ensure privacy protection during network service utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network services use privacy-related information (such as location data) to provide accurate analytics and services, then service quality and accuracy are improved, but user privacy protection deteriorates
Solution Approach 1:
The patent introduces privacy models as intermediary components that mediate between the service consumer's privacy-related information and the network service. The privacy model processes and transforms the original privacy information into protected representations, allowing the network service to obtain useful analytics while the user's actual privacy data remains protected. This intermediary mechanism resolves the contradiction by decoupling the need for accurate service delivery from direct exposure of sensitive user information.
Solution Approach 2:
The patent transforms privacy-related information through parameter changes by applying privacy models that modify the data representation. The privacy model changes the parameters of the original data (such as location information) into protected forms that retain service utility while removing or obscuring personally identifiable characteristics. This parameter transformation allows service accuracy to be maintained through the transformed data while the original privacy-sensitive parameters are protected.
2Adaptability or versatility
If network services collect and process detailed user information to improve service quality, then service functionality is enhanced, but data security and user control deteriorate
Solution Approach 1:
The patent implements self-service through the privacy model that autonomously processes and protects privacy-related information without requiring continuous user intervention. The service consumer configures the privacy model with their preferences and constraints, and the model then automatically applies the appropriate protection mechanisms to the data being shared with network services. This self-service approach enhances service functionality by enabling automated privacy protection while maintaining data security through consistent application of protection rules.
Solution Approach 2:
The patent incorporates feedback mechanisms where the service consumer can provide input about their privacy preferences and receive feedback on how their data is being protected. The privacy model processes this feedback and adjusts the protection level accordingly, creating a closed-loop system that continuously improves both service functionality and data security. The feedback loop ensures that user control is maintained while service adaptability is enhanced through iterative refinement of privacy protection strategies.
3Extent of automation
If AI/ML-based services are deployed to enhance network capabilities, then service intelligence is improved, but privacy risks and complexity increase
Solution Approach 1:
The patent segments the complex AI/ML service system into distinct functional components: the service consumer, the privacy model, and the network service provider. Each segment has a specific responsibility - the consumer provides data and preferences, the privacy model processes and protects the information, and the provider delivers the intelligent service. This segmentation reduces overall system complexity by creating modular, independently manageable components while maintaining high service intelligence through the coordinated operation of these segments.
Solution Approach 2:
The patent applies preliminary action by implementing privacy protection mechanisms before the AI/ML processing occurs. The privacy model is applied in advance to transform and protect the privacy-related information before it is used by the AI/ML-based network service. This preliminary protection action reduces the complexity of managing privacy risks throughout the entire AI/ML processing pipeline, as the data is already protected when it enters the intelligent processing stage.
Data Source
AI summary
A method for operating a service consumer which is requesting to utilize a network service provided by a service provider in a cellular network. The method includes, at the service consumer, transmitting a service request to the service provider, the service request including a privacy indication indicating that a privacy related information necessary as input for the network service is requested to be privacy protected when used outside the service consumer, receiving a service response from the service provider, the service response comprising a privacy model and an indication how to use the privacy model, and processing the privacy model at the service consumer based on the indication.