TEE Sandbox Workflows for Secure Digital Component Selection
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Solution Overview
Problem
Existing systems fail to securely execute proprietary customization workflows while preserving user privacy and system integrity, as they often expose sensitive user data and proprietary logic to unauthorized access.
Innovation Solution
Implementing workflows in isolated environments, such as virtual machines or trusted execution environments (TEEs), with sandboxes to execute customizable stages, ensuring that user data and proprietary logic remain confidential and secure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-stage workflows are executed in separate sandbox environments using trusted execution environments, then data security and privacy protection are improved, but system complexity and computational overhead increase
Solution Approach 1:
The system divides the workflow execution into multiple isolated sandbox environments, each handling specific stages of data processing. These sandboxes are further segmented by data sensitivity levels (L1-L4), creating a hierarchical structure where each segment operates independently with appropriate security controls, thus managing complexity through structured division while maintaining high security.
Solution Approach 2:
The trusted execution environment (TEE) acts as an intermediary layer between the workflow engine and the underlying hardware infrastructure. This intermediary provides hardware-enforced isolation and security controls, allowing complex security operations to be abstracted away from the application layer, thereby improving security without proportionally increasing system complexity for end users.
2Reliability
If multi-stage workflows are executed in separate sandbox environments using trusted execution environments, then privacy protection for sensitive data is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary classification of data into sensitivity levels (L1-L4) before workflow execution begins. This preliminary action allows the workflow engine to pre-determine which sandbox environment will handle each data element, avoiding runtime security checks and enabling more efficient processing while maintaining privacy protection through appropriate isolation.
Solution Approach 2:
The sandbox environment allocation is dynamic rather than static. The workflow engine can adjust which sandbox handles which workflow stage based on real-time factors such as data sensitivity level, available computational resources, and workflow priorities. This dynamic allocation optimizes processing time while maintaining privacy protection by flexibly matching security requirements with available resources.
3Reliability
If multiple sandbox environments are used for different workflow stages, then security control over data processing is improved, but device complexity and resource requirements increase
Solution Approach 1:
The TEE infrastructure provides universal security controls that can be applied across multiple sandbox environments. Rather than implementing separate security mechanisms in each sandbox, the system uses a unified TEE layer that enforces security policies across all sandboxes, reducing redundant resource consumption while maintaining strong security controls throughout the system.
Solution Approach 2:
The system changes security parameters dynamically based on data sensitivity levels. Instead of applying maximum security controls uniformly across all workflows, the system adjusts security parameters (such as isolation strength, access controls, and monitoring intensity) according to the classified sensitivity level of each data element, optimizing the balance between security control and resource consumption.
Data Source
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AI summary
A computer-implemented method is disclosed, comprising: receiving, from a client device, a digital component request (125) comprising a set of data; in response to receiving the digital component request (125): identifying multi-stage workflows (240) associated with content platforms; executing, by a trusted execution environment, TEE, (205) of a computer, one or more stages of each multi-stage workflow in a separate sandbox environment, wherein each multi-stage workflow is configured to generate output data comprising selection parameters for candidate digital components based on at least a portion of the set of data; and receiving the output data from the sandbox environment for each multi-stage workflow; selecting, by the computer, a digital component based on at least a portion of the output data from each multi-stage workflow (240); and providing, by the computer, the selected digital component to the client device for presentation to a user of the client device.