Cloud Device Onboarding with Trust Metrics for Hardware Changes
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Solution Overview
Problem
Existing cloud management systems face inefficiencies in scalable and secure onboarding processes for out-of-band devices, particularly due to manual processes and insecure configurations during device ownership claims, leading to compromised cloud tenant states.
Innovation Solution
Implementing a hybrid cloud management platform with a trusted cloud device lifecycle management component for secure, remotely-attested out-of-band device lifecycle management, including secure onboarding, renewal, and decommissioning, using unique root of trust keys and inventory data for verification and attestation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual onboarding processes are used for out-of-band devices, then device configuration flexibility is improved, but security reliability deteriorates due to insecure configurations during device ownership claims
Solution Approach 1:
The patent introduces a cloud management system as an intermediary between devices and cloud services. This intermediary automatically manages device onboarding, configuration, and lifecycle operations, eliminating manual security risks while maintaining configuration flexibility. The cloud management system acts as a trusted mediator that enforces security policies during device ownership claims and configuration changes.
Solution Approach 2:
The system performs preliminary security verification and configuration validation before devices are fully onboarded. Trust metrics are evaluated in advance during the onboarding process, and security configurations are pre-established before devices access cloud resources. This preliminary action ensures security requirements are met before operational flexibility is granted.
2Reliability
If automated trust verification is implemented for device onboarding, then security reliability is improved, but processing time increases due to hardware configuration verification
Solution Approach 1:
Device hardware configurations are verified and trust metrics are evaluated in advance during the onboarding process. Security attributes are pre-assessed and stored, allowing for rapid subsequent verification. This preliminary action moves time-consuming verification steps before device activation, enabling faster processing during actual operations.
Solution Approach 2:
The system creates and stores copies of device hardware configuration data and trust metrics during onboarding. These copied verification results are then used for rapid subsequent authentication and trust verification, eliminating the need to repeatedly perform full hardware verification. The copied data enables fast comparison and validation without re-accessing physical devices.
3Measurement precision
If continuous monitoring of hardware component changes is performed, then trust metrics accuracy is improved, but system complexity increases
Solution Approach 1:
Devices perform self-reporting of their hardware configuration changes to the cloud management system. The monitored devices automatically provide updates about their own component changes, eliminating the need for complex external monitoring infrastructure. This self-service approach maintains accurate trust metrics while reducing overall system complexity by distributing the monitoring function to the devices themselves.
Solution Approach 2:
The system implements a feedback mechanism where devices report hardware changes and the cloud management system updates trust metrics accordingly. This continuous feedback loop maintains accurate trust information without requiring complex proactive monitoring. The feedback-based approach simplifies the system by using event-driven updates rather than continuous active scanning.
Data Source
AI summary
A system can receive an untrusted onboard announcement message from a remote computer, wherein the untrusted onboard announcement message comprises first data that identifies the remote computer and second data that indicates a current configuration of the remote computer. The system can identify a stored indication of an authorized configuration of the remote computer based on the data that identifies the remote computer. The system can determine that there is a mismatch between the authorized configuration of the remote computer and the current configuration of the remote computer. The system can determine a trust metrics evaluation score for the remote computer based on a type of hardware component change between the authorized configuration of the remote computer and the current configuration of the remote computer. The system can, in response to determining that the trust metrics evaluation score is greater than a threshold value, onboard the remote computer.