Reputation Module Combining Multiple Reputations

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Solution Overview

Problem

Existing solutions for determining device and network reputations require frequent updates, making them expensive and inefficient, and fail to incorporate arbitrary end-user generated reputations effectively.

Innovation Solution

A communication system that combines multiple reputations using a Bayesian algorithm with probabilistic math, external weights, and confidence normalization, allowing for the inclusion of backend, service provider, and external reputations, and enabling the calculation of a final trust score with remediation flags.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If frequent updates are performed to maintain accurate reputation data, then the reliability of reputation assessment is improved, but the cost and resource consumption increase

Engineering Contradiction:

Improvereputation assessment accuracyVSAvoidupdate cost

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system enables end users to self-generate reputation data for their own objects without requiring external verification or frequent system-wide updates. Each user maintains and updates their own reputation information, eliminating the need for centralized frequent updates while maintaining data freshness and accuracy.

Inventive Principle:

Principle #25Self-service

2Loss of information

If multiple reputation sources are integrated to provide comprehensive assessment, then the completeness of reputation data is improved, but the system complexity increases

Engineering Contradiction:

Improvereputation data completenessVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system merges multiple reputation sources (backend reputations, service provider reputations, and external reputations) into a unified reputation framework. By combining these diverse reputation data sources, the system achieves comprehensive reputation assessment while managing complexity through a standardized integration approach that allows end-user generated reputations to be incorporated alongside other sources.

Inventive Principle:

Principle #5Merging (Combining)

3Adaptability or versatility

If end-user generated reputations are incorporated to increase data availability, then the versatility of the system is improved, but the difficulty of managing and validating data increases

Engineering Contradiction:

Improvereputation source flexibilityVSAvoiddata validation difficulty

Core Design Contradiction:

Adaptability or versatilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system introduces an intermediary validation mechanism that processes end-user generated reputation data before integrating it into the overall reputation framework. This intermediary layer validates and standardizes user-generated reputations, ensuring data quality and consistency while maintaining the flexibility to incorporate diverse end-user data sources without overwhelming system complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS10083295B2System and method to combine multiple reputations

Publication Date: 2018.09.25 MCAFEE LLC

AI summary

Particular embodiments described herein provide for an electronic device that can be configured to acquire a plurality of reputations related to an object and combine the plurality of reputations to create a total reputation for the object. The object can include a plurality of sub-objects and each of the plurality of reputations can correspond to one of the sub-objects.