Context-Aware API Security System for Dynamic Rate Limiting
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Solution Overview
Problem
Existing firewalls are inadequate in protecting remotely accessed Application Programming Interfaces (APIs) from misuse or attacks, as they rely on static rules and may incorrectly block valid API traffic.
Innovation Solution
The implementation of a system that models contextual relationships between API context and user context to dynamically enforce customized rules and policies for each API function, distinguishing between proper and improper usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static rate limiting rules are used to protect APIs, then security protection is provided, but valid API traffic is incorrectly blocked
Solution Approach 1:
The patent implements dynamic rate limiting by transitioning from static rules to context-aware policies that adapt based on API endpoint characteristics, user behavior patterns, and real-time usage conditions. The system learns normal usage patterns for different endpoints and dynamically adjusts rate limits accordingly, allowing high-frequency legitimate calls while blocking anomalous traffic.
Solution Approach 2:
The system changes the parameters of rate limiting from fixed values to context-dependent variables. Rate limits are no longer uniform but are customized per API endpoint, user, and usage pattern based on learned behavioral parameters. This allows the system to accommodate varying legitimate usage rates while maintaining security thresholds.
2Ease of manufacture
If uniform security rules are applied to all API endpoints, then implementation simplicity is maintained, but API-specific security requirements are not met
Solution Approach 1:
The patent segments security policies by API endpoint, user, and usage context rather than applying uniform rules. Each API endpoint receives customized rate limiting and security parameters based on its specific requirements, data sensitivity, and usage patterns. This segmentation enables tailored security without requiring manual configuration of each policy.
Solution Approach 2:
The system automatically generates customized security policies for different API endpoints through machine learning and behavioral analysis. Rather than requiring manual security configuration for each endpoint, the system self-learns usage patterns and automatically creates appropriate security rules, reducing implementation complexity while maintaining customization.
3Reliability
If context-aware dynamic policies are implemented, then API-specific security is enhanced, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary security layer that sits between the API gateway and backend services. This intermediary component handles the complexity of context-aware policy enforcement, behavioral analysis, and dynamic rule generation, shielding the core API infrastructure from complexity while providing enhanced security. The intermediary translates complex security requirements into actionable enforcement decisions.
Data Source
AI summary
Disclosed is a system for customizing protections provided to different application programming interfaces (“APIs”) and different functions of an API based on different API context and user context associated with the different APIs and the different functions of each API. The system receives a particular API, determines API context for proper usage of one or more functions of the particular API, and determines user context associated with endpoints properly accessing the one or more functions. The system generates a model for differentiating between proper and improper use of the one or more functions based on contextual relationships between different combinations of the API context and the user context. The system monitors usage of the one or more functions based on the model, and performs an action that is associated with the model in response to the usage violating the contextual relationships for the one or more functions.