Autonomous Trust Evaluation Engine for Private Data Access Control
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Solution Overview
Problem
Users face challenges in controlling access to their private data due to the lack of trustworthiness evaluation of entities requesting access, leading to concerns about privacy and data security in the increasing volume of data generated by new technologies.
Innovation Solution
An autonomous trust evaluation engine computes a trust rating for data requesters across various dimensions, using external sources such as social media and review sites, to grant or deny access to user private data, allowing users to set and enforce security policies based on their selected criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If access control policies are implemented without trustworthiness evaluation, then data access efficiency is improved, but data security and privacy protection deteriorate
Solution Approach 1:
The system performs trustworthiness evaluation in advance before granting data access. Trust ratings are computed for data requesters across multiple dimensions (confidentiality, integrity, authenticity, compliance, availability) using information from external sources, so that when access requests occur, the evaluation is already complete and access decisions can be made efficiently based on pre-established trust levels.
Solution Approach 2:
The patent introduces a trust evaluation engine as an intermediary component between data requesters and data. This engine autonomously computes trust ratings and provides a mediating layer that assesses requesters before access is granted, thereby enabling security verification without directly blocking the access flow.
2Reliability
If comprehensive trust evaluation is performed across multiple dimensions, then data security is improved, but system complexity increases
Solution Approach 1:
The trust evaluation system is segmented into distinct dimensions: confidentiality, integrity, authenticity, compliance, and availability. Each dimension is evaluated separately using specific criteria and data sources, allowing the complex evaluation process to be broken down into manageable, independent components that can be processed systematically.
Solution Approach 2:
The trust evaluation engine autonomously collects information from external sources, computes trust ratings across multiple dimensions, and makes access decisions without requiring manual intervention. The system self-manages the entire evaluation process, reducing operational complexity despite the comprehensive nature of the assessment.
3Measurement precision
If multiple external sources are used for trust rating computation, then measurement precision is improved, but information collection complexity increases
Solution Approach 1:
The trust evaluation engine is designed to universally collect and process information from multiple types of external sources (social media, review sites, other data sources) using a unified approach. The same evaluation framework handles different source types, allowing the system to leverage diverse information sources without requiring separate collection mechanisms for each source type.
Data Source
AI summary
A trust rating is computed for a data requester across one or more dimensions by identifying the data requester, collecting information regarding the data requester from one or more sources, and generating the trust rating for the data requester across the one or more dimensions based on the collected information. The trust rating is utilized to either grant or deny a request by the data requester to access data associated with one or more data providers.