Network Function Trust Evaluation Service
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Solution Overview
Problem
Wireless communication networks face security attacks that impact user equipment operations, and existing technologies lack effective methods for evaluating and ensuring trust within these networks.
Innovation Solution
The implementation of a trust evaluation service at a network function (NF) that involves receiving request messages, performing inference data collection, and conducting trust evaluations to produce trust evaluation data, which is then transmitted to other NFs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If trust evaluation services are implemented at network functions to continuously validate trust and detect security breaches, then network security and reliability are improved, but device complexity and operational overhead increase
Solution Approach 1:
The trust evaluation functionality is segmented into separate network functions (trust evaluation NF and consumer NFs) that can independently operate. The trust evaluation NF collects data from multiple sources and produces trust scores that are consumed by other NFs, creating a modular architecture that reduces complexity in individual components while maintaining comprehensive security monitoring.
Solution Approach 2:
A trust evaluation network function acts as an intermediary between data collectors and trust consumers. This intermediary collects inference data from various network functions, processes it through evaluation algorithms, and distributes trust scores to relevant NFs, thereby centralizing complexity in a dedicated component rather than distributing it throughout the entire network.
2Difficulty of detecting and measuring
If inference data collection is performed continuously to enable real-time trust evaluation, then detection capability is improved, but energy consumption and processing resources increase
Solution Approach 1:
The system collects inference data from multiple network functions rather than all possible data sources, and processes only the necessary parameters for trust evaluation. This partial action approach enables real-time detection capability while minimizing the energy and processing resources required compared to comprehensive continuous monitoring of all network parameters.
Solution Approach 2:
Different network functions collect and process inference data locally based on their specific roles and the trust relationships they manage. This localized data collection and processing reduces the need for all NFs to continuously monitor everything, thereby reducing overall energy consumption while maintaining effective threat detection capabilities.
Data Source
AI summary
Apparatuses, methods, and systems are disclosed for performing a trust evaluation service at a network function (“NF”). One method includes receiving, at a first NF, a first request message from a second NF. The first request message includes a trust service subscription request message corresponding to a trust service subscription. The method includes performing inference data collection. The method includes performing a trust evaluation service corresponding to the trust service subscription to produce trust evaluation data. The trust evaluation service is performed based at least in part on the inference data collected. The method includes transmitting a first response message to the second NF. The first response message includes information corresponding to the trust evaluation data.