Container Profile Merging via Context Segmentation
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Solution Overview
Problem
Existing container environments require a black box analysis by hosts to provide safe and optimized profiles, which lacks accuracy and security, as development groups only provide images without detailed context, leading to inadequate security and resource management.
Innovation Solution
A method to extract sensitive and insensitive contexts from both developer and host profiles, merging them to generate a final profile that applies the host's security policy and extends resources according to developer needs, using a developer context extractor, host context extractor, max configuration extractor, and final profile generator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If black box analysis is used by hosts to provide profiles, then security constraints are applied, but accuracy and security are insufficient due to lack of detailed context
Solution Approach 1:
The profile information is segmented into sensitive context (security-related) and insensitive context (non-security-related), allowing separate handling and merging of developer and host profiles to achieve both accuracy and security
Solution Approach 2:
The developer profile and host profile are merged to generate a final profile that combines the detailed context from the developer with the security constraints from the host, resolving the contradiction between accuracy and security
2Measurement precision
If detailed context from developer is integrated with host profile, then analysis accuracy improves, but system complexity increases
Solution Approach 1:
By segmenting profile information into sensitive and insensitive contexts, the system manages complexity through structured organization rather than handling all context uniformly
Solution Approach 2:
The profile merging mechanism acts as an intermediary that systematically integrates developer and host profiles, managing the complexity of combining detailed context with security constraints
Data Source
AI summary
Provided is a design method for sharing a profile in a container environment, including: extracting a sensitive context defined as information related to system-based access control or a sandboxing policy and an insensitive context defined as information unrelated to security for a profile provided by a developer; extracting the sensitive context and the insensitive context for the profile provided by a host; fetching a max configuration for the sensitive and insensitive contexts from each image layer of the developer; and generating a final profile that is applied to deploy the container by merging the host profile with the max configuration fetched from the developer profile. Accordingly, it is possible to provide an optimal environment to developers and hosts by generating the final profile with a hierarchical model using the host profile and the developer profile.