Compositional Reasoning for Cloud Role Reachability
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Solution Overview
Problem
Cloud provider networks face challenges in efficiently managing role reachability across large-scale, complex identity and access management systems, where thousands of accounts and roles require secure access control to prevent unauthorized access and ensure compliance, especially with the exponential growth of cloud-based services.
Innovation Solution
The implementation of compositional reasoning techniques for role reachability analyses, which enable the identity and access management service to programmatically reason about interactions between various policy types and distribute the analysis across multiple computing resources, improving computational performance and memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional role reachability analysis methods are used in large-scale cloud provider networks, then security and access control can be maintained, but computational performance deteriorates and memory usage increases due to the exponential growth of accounts and roles
Solution Approach 1:
The patent segments the role reachability analysis into multiple independent parts by dividing the policy graph into account-level subgraphs. Each subgraph represents a specific account's roles and policies, allowing parallel processing across multiple computing resources. This segmentation enables the system to maintain comprehensive security analysis while improving computational performance through distributed processing.
Solution Approach 2:
The patent introduces a hierarchical dimension to the analysis by organizing roles and policies across multiple accounts in a tree-like structure. This dimensional organization allows the system to navigate and process large-scale identity management data more efficiently, reducing memory usage and improving computational performance while maintaining thorough security checks.
2Reliability
If comprehensive role reachability analysis is performed across all accounts and roles, then security posture is enhanced, but memory usage and computational resources increase
Solution Approach 1:
The patent divides the comprehensive role reachability analysis into smaller, manageable subgraphs corresponding to individual accounts. Each subgraph contains only the roles and policies relevant to that specific account, allowing the system to perform thorough security analysis without loading all data into memory simultaneously. This segmentation significantly reduces memory requirements while maintaining comprehensive security posture.
Solution Approach 2:
The patent applies partial analysis by focusing role reachability analysis on specific accounts or role sets rather than uniformly analyzing all accounts. This selective approach allows the system to maintain strong security posture for critical accounts while reducing overall computational and memory resources consumed during analysis.
Data Source
AI summary
Techniques are described for using compositional reasoning techniques to perform role reachability analyses relative to collections of user accounts and roles of a cloud provider network. Delegated role-based resource management generally is a method for controlling access to resources in cloud provider networks and other distributed systems. Many cloud provider networks, for example, implement identity and access management subsystems using this approach, where the concept of “roles” is used to specify which resources can be accessed by people, software, or (recursively) by other roles. An abstraction of the role reachability analysis is provided that can be used as input to a model-checking application to reason about such role reachability questions (e.g., which roles of an organization are reachable from other roles).