Trust-Score Data Filtering in Service-Mesh Microservices

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Solution Overview

Problem

Existing service mesh architectures lack effective dynamic data filtering mechanisms to ensure secure data transfer between microservices based on varying levels of trust, leading to potential security breaches and compromised confidentiality.

Innovation Solution

Implementing a computer-implemented method within a service mesh that evaluates trust scores between microservices to determine which data to filter, queue, or reject, ensuring secure data transfer by adjusting security measures based on trust levels.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data filtering is implemented based on trust scores, then network security and data confidentiality are improved, but data transfer efficiency and system productivity deteriorate due to filtering delays

Engineering Contradiction:

Improvenetwork securityVSAvoiddata transfer efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system dynamically adjusts filtering behavior based on real-time trust score changes. When a microservice's trust score increases above a threshold, the filtering intensity is reduced or suspended, allowing faster data transfer. When trust scores decrease, filtering intensifies. This dynamic adaptation resolves the contradiction by making security measures flexible rather than static.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the parameter of trust score thresholds to control filtering behavior. By adjusting threshold values and filtering intensity levels based on trust score magnitude, the system can optimize between security and efficiency. High trust scores result in lower filtering intensity (higher efficiency), while low trust scores trigger strict filtering (higher security).

Inventive Principle:

Principle #35Parameter changes

2Reliability

If strict data filtering is applied to all data transfers, then data confidentiality is improved, but system complexity and operational overhead increase

Engineering Contradiction:

Improvedata confidentialityVSAvoidfiltering mechanism complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system applies different filtering qualities to different data transfers based on local trust conditions. Each microservice evaluates its own trust score and applies appropriate filtering locally, rather than using a uniform strict filter everywhere. This localized approach reduces overall system complexity while maintaining confidentiality where needed.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

Each microservice autonomously evaluates its own trust score and makes filtering decisions independently, without requiring centralized complex filtering logic. The self-service mechanism simplifies system architecture by distributing the filtering intelligence to individual services based on their own trust assessments.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12423429B2Dynamic data filtering based on trust score within service mesh

Publication Date: 2025.09.23 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer-implemented method performs dynamic filtering within a service mesh. While transferring data from one microservice to another microservice, each microservice evaluates a level of trust with each upstream and downstream microservice based on the level of trust score. Each microservice evaluates which data should be filtered while transferring data to downstream microservice and which data should be filtered while receiving data from upstream microservice.