Shadow SMT Solvers for Cloud Policy Verification Accuracy
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Solution Overview
Problem
Satisfiability modulo theories (SMT) solvers in cloud provider networks face challenges in verifying correctness and comparing performance across different solvers, leading to potential inaccuracies and inefficiencies in policy analysis and resource management.
Innovation Solution
Deploying 'shadow' SMT solver systems alongside primary solvers to run experiments and assess accuracy and performance by comparing results from multiple solvers, including different portfolios and versions, ensuring accurate and efficient policy evaluations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single primary SMT solver system is used for policy analysis, then the system operation is simple and fast, but the accuracy and reliability of policy verification cannot be ensured
Solution Approach 1:
The patent creates shadow copies of SMT solver systems that replicate the primary solver's structure and behavior. These shadow solvers process the same policy analysis queries and their results are compared against the primary solver's outputs to detect inaccuracies, thereby improving verification reliability without requiring multiple different solver types
Solution Approach 2:
The shadow SMT solver systems provide feedback by comparing their results with the primary solver's results. When discrepancies are detected, the system can alert operators or automatically adjust the policy analysis process, creating a feedback loop that improves the overall reliability of policy verification
2Measurement precision
If multiple SMT solver systems are deployed to compare results, then the accuracy and performance assessment improve, but the computational time and resource consumption increase
Solution Approach 1:
The system employs shadow solvers that perform partial computations by focusing only on the differences or uncertainties in policy analysis results. Rather than completely independent full computations, the shadow solvers target specific verification tasks that would catch errors in the primary solver, reducing overall computational time while maintaining measurement precision
Solution Approach 2:
The shadow SMT solver systems are configured to perform preliminary verification tasks before final policy analysis conclusions are drawn. By pre-checking results against shadow solvers, the system can identify and correct potential errors early in the process, reducing the need for time-consuming reanalysis
Data Source
AI summary
Techniques are described for executing satisfiability modulo theories (SMT) solvers in a “shadow” system configuration where input queries are provided to a primary SMT solver system and additionally to one or more secondary SMT solver systems. SMT solver systems can be used by cloud providers and in other computing environments to analyze the implications of configured user account policies defining permissions with respect to users' computing resources and associated actions within a computing environment, to help ensure the security of computing resources and user data, etc. The results generated by a primary SMT solver system can be provided to one or more secondary SMT solver systems, where each of the secondary SMT systems can comprise different system components or different versions of system components, to assess the correctness of the primary SMT solver system, to compare performance metrics, among other possible types of analyses.