Verified Policy Compilation for Low-Latency Access Decisions
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Solution Overview
Problem
Existing identity and access management systems face challenges with scalability and performance, particularly in the evaluation of access requests by the Policy Decision Point (PDP), leading to increased latency and potential bottlenecks that affect user experience and application quality.
Innovation Solution
Implementing policy optimization and verified policy compilation techniques, including pre-computing certain policy sections (residual policies) and transforming policies into an efficient format, to reduce latency and improve evaluation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronous policy evaluation is used to ensure accurate access control decisions, then policy enforcement reliability is improved, but request latency increases and processing throughput decreases
Solution Approach 1:
The patent pre-computes and caches policy evaluation results before they are actually needed. The PDP evaluates policies in advance and stores the results in a cache, so when access requests arrive, the decisions can be retrieved quickly without performing full synchronous evaluation at request time, thus reducing latency while maintaining accuracy.
Solution Approach 2:
The patent segments the policy evaluation process into distinct phases: pre-computation phase where policies are evaluated in advance, caching phase where results are stored, and retrieval phase where cached results are used for actual requests. This segmentation allows the system to separate the computationally intensive evaluation from the time-critical request handling.
2Reliability
If synchronous policy evaluation is performed to ensure correct authorization decisions, then policy decision accuracy is improved, but processing throughput and pipeline capacity deteriorate
Solution Approach 1:
Policy evaluations are performed in advance and results are cached before actual access requests need to be processed. This preliminary computation allows the system to maintain high decision accuracy while achieving high throughput during actual request handling, as the expensive evaluation work has already been completed.
Solution Approach 2:
The patent creates cached copies of policy evaluation results that can be rapidly retrieved and used multiple times. Instead of re-evaluating policies for each request, the system uses copied results from the cache, dramatically increasing processing throughput while maintaining the accuracy of the original evaluations.
3Speed
If policy optimization and compilation are implemented to reduce evaluation time, then request processing speed is improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The system performs policy compilation and optimization in advance, transforming policies into an efficient intermediate representation before they are needed for actual request processing. This preliminary preparation reduces the complexity of real-time processing while maintaining high speed, as the heavy transformation work is done beforehand.
Data Source
AI summary
Techniques include using a verified access control policy compiler to compile a first access control policy into a compiled form. This compiled policy is then indexed. When an access request is received, the method retrieves the compiled policy from the index using attributes of the access request. The access request is evaluated against the compiled policy to determine authorization, and the resulting decision is returned. This process streamlines the evaluation and authorization decision-making process, making it more efficient.