Zero-Trust Resource Trust Scoring Using Telemetry and Policy Feedback
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Solution Overview
Problem
Existing zero-trust computing environments lack a systematic approach to evaluate and dynamically adjust trust levels for resources based on user, hardware, software, network, and data interactions, leading to suboptimal access control and security.
Innovation Solution
A trust scoring framework that calculates trust scores for resources in a zero-trust environment by considering user, hardware, software, and network interactions, adjusting scores based on telemetry and policy updates, and enforcing access control decisions using a policy decision point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional access control methods are used in zero-trust environments, then implementation simplicity is maintained, but security effectiveness deteriorates due to lack of dynamic trust evaluation
Solution Approach 1:
The access control system is segmented into multiple independent trust score calculators, each responsible for evaluating specific aspects (user behavior, hardware integrity, software compliance, network security). This segmentation allows the complex evaluation process to be divided into manageable components while maintaining overall security effectiveness.
Solution Approach 2:
The system implements dynamic trust scoring where access permissions are not static but continuously adjusted based on real-time evaluation of multiple factors. Trust scores are recalculated periodically and updated dynamically, allowing the system to adapt to changing security conditions without requiring complete reauthentication.
2Reliability
If continuous validation of all access requests is implemented, then security posture is improved, but processing time increases
Solution Approach 1:
The system performs partial validation by focusing trust score evaluation on the most critical risk factors rather than exhaustively checking every possible parameter. High-risk requests trigger more comprehensive validation, while low-risk requests undergo streamlined evaluation, reducing overall processing time while maintaining security effectiveness.
Solution Approach 2:
The system implements feedback mechanisms where trust scores from previous evaluations are used to inform subsequent validation decisions. Established trust patterns allow the system to make faster decisions for routine requests, while anomalies trigger deeper validation, creating a feedback loop that improves both speed and accuracy over time.
3Measurement precision
If multiple trust score factors are evaluated, then measurement precision is improved, but calculation complexity increases
Solution Approach 1:
Different aspects of trust evaluation are assigned different weights and levels of scrutiny based on their local importance. Critical factors such as hardware integrity and user authentication receive higher precision evaluation, while less critical factors undergo simpler assessment. This local quality approach allows precise measurement where needed without uniformly increasing complexity across all evaluation dimensions.
Data Source
AI summary
Methods and systems are included for evaluating trust in resources of a zero-trust computing environment. A request is received from a user for access to a resource of the zero-trust environment. A trust score is calculated for the resource based on: users requesting access to the resource, hardware components used to request access to the resource, software applications used to request access to the resource, networks used to request access to the resource and data exposed by providing the requested access to the resource. The request from the user is evaluated based on policies of the zero-trust environment that govern access to the resource, where policies grant or deny access to the resource based in part on the calculated trust score of the resource.