Policy Rule Anomaly Detection via Mixed-Radix Truth Tables
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Solution Overview
Problem
Modern computing systems face challenges in identifying and correcting errors and inconsistencies in policies governing administrative, business, and regulatory requirements across different domains, making it difficult to ensure accurate control of access to information and capabilities.
Innovation Solution
A method and system for examining policies in an enterprise system by representing policy rules as conditions with binary operator expressions, using mixed-radix enumeration to generate truth tables, and detecting anomalies by comparing these tables, thereby alerting users to inconsistencies and errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If policies are represented as separate authoring systems for different policy types, then policy specification flexibility is improved, but policy consistency and error detection capability deteriorates
Solution Approach 1:
The patent applies universality by creating a unified policy representation framework that can handle multiple policy types (access control, QoS, network management, etc.) through a common structure. The system uses a standardized policy rule format with conditions, actions, and expressions that can represent different policy domains, enabling consistent analysis across diverse policy types while maintaining the flexibility needed for each specific domain.
Solution Approach 2:
The patent introduces an intermediary analysis system that acts as a mediator between separately authored policies and the target system. This intermediary component performs consistency checking, anomaly detection, and validation by analyzing policy rules before they are deployed, thereby ensuring policy consistency without restricting the flexibility of separate policy authoring systems.
2Reliability
If comprehensive policy checking is performed to detect all errors and inconsistencies, then policy reliability is improved, but computational complexity and analysis time increases
Solution Approach 1:
The patent applies segmentation by dividing the policy analysis process into distinct modular components: policy parsing, expression evaluation, truth table generation, anomaly detection, and reporting. Each component handles a specific aspect of policy validation, making the overall complex analysis task manageable and maintainable while ensuring comprehensive error detection through systematic processing of policy rules.
Solution Approach 2:
The patent implements partial action by focusing the analysis system on detecting specific types of anomalies and inconsistencies that are most critical for policy reliability, rather than attempting to analyze every possible aspect of policies. The system performs targeted checking on policy conditions, expressions, and rule conflicts, providing sufficient validation without requiring exhaustive analysis of all potential policy attributes.
3Measurement precision
If detailed truth table analysis is performed on all policy expressions, then anomaly detection precision is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by performing early validation and simplification of policy expressions before generating truth tables. The system pre-processes policy rules to identify obviously valid or invalid expressions, simplifies logical conditions where possible, and prioritizes analysis of critical policy areas, thereby reducing the overall computational burden while maintaining detection precision for significant anomalies.
Solution Approach 2:
The patent implements local quality by applying different levels of analysis depth to different parts of the policy set. Critical policy rules that have greater impact on system security and operation receive more thorough truth table analysis, while less critical rules undergo lighter validation. This differentiated approach maintains high detection precision for important anomalies while reducing processing time for the overall policy set.
Data Source
AI summary
A computer-performed method of examining policies for a target system of an enterprise system domain. The policies are represented as policy rules, each rule including a condition having binary operator expression(s), each expression referring to one or more policy attributes. For a pair of expressions, the computer(s) obtain sets of sample values sufficient to represent all values assumable by the policy attribute(s) referred to in the pair. The sample values are combined in a mixed-radix enumeration in which each attribute is represented in a corresponding position of each sample value combination and of the enumeration. Using the enumeration, the computer(s) evaluate each expression of the pair relative to each of the sample value combinations to obtain a truth table. Based on the truth table, a relationship between the pair is detected and the user may be notified as to an anomaly in the rules.