IaC Deployment Validation With TEE for Secure Cloud Configurations
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Solution Overview
Problem
Cloud customers lack mechanisms to ensure security against malicious CSP-backdoors or configuration drifts in cloud environments, compromising trust in cloud service providers.
Innovation Solution
Implement a trusted execution environment (TEE) and secure configuration parameters in Infrastructure as Code (IaC) templates to validate and enforce security rules, ensuring that infrastructure configurations adhere to user-defined security intentions and monitor runtime compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a trusted execution environment with FPGA and secure I/O transactions is implemented to validate infrastructure configurations, then security and reliability are improved, but device complexity increases
Solution Approach 1:
The patent introduces a trusted execution environment (TEE) with FPGA as an intermediary component between the cloud service provider and cloud customers. This TEE validates infrastructure configurations and enforces security rules, acting as a mediator that provides cryptographic proof of configuration integrity without requiring full trust in the CSP. The secure I/O transactions with authentication tags further mediate data transfer security.
Solution Approach 2:
The system segments the trust verification process into distinct components: the TEE validates infrastructure configurations separately, the FPGA handles cryptographic operations independently, and secure I/O transactions verify data integrity separately. This segmentation allows each component to specialize in specific security functions, improving overall reliability while making the complex system more manageable through modular architecture.
2Reliability
If security validation mechanisms are implemented in IaC deployments, then protection against malicious backdoors and configuration drifts is improved, but ease of operation deteriorates
Solution Approach 1:
The trusted execution environment performs self-service validation by automatically verifying infrastructure configurations against security rules without requiring manual intervention from cloud customers. The TEE autonomously executes validation logic, generates cryptographic proofs, and enforces security policies, thereby maintaining ease of operation while providing robust security assurance.
Solution Approach 2:
The system implements feedback mechanisms where the TEE continuously monitors infrastructure configurations and provides validation results back to the deployment process. Security rules are enforced through automated feedback loops that detect configuration drifts and malicious backdoors, allowing the system to self-correct without complicating the operational workflow for users.
3Reliability
If cryptographic operations and authentication tags are used to secure I/O transactions, then reliability is improved, but use of energy increases
Solution Approach 1:
The patent replaces traditional software-based cryptographic validation with hardware-based cryptographic operations in the FPGA and TEE. This substitution moves cryptographic functions from general-purpose processors to specialized hardware circuits, significantly reducing the energy required for cryptographic operations while maintaining data integrity and authentication tag verification.
Solution Approach 2:
The system changes the operational parameters of cryptographic operations by executing them in a trusted execution environment with dedicated hardware resources. This parameter change from software to hardware execution mode reduces computational overhead and energy consumption while improving the reliability of cryptographic validation for secure I/O transactions.
Data Source
AI summary
A computing platform comprising a plurality of disaggregated data center resources and an infrastructure processing unit (IPU), communicatively coupled to the plurality of resources, to compose a platform of the plurality of disaggregated data center resources for allocation of microservices cluster.