Risk-Level Rule Sets for Low-Latency Service Access Control
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Solution Overview
Problem
Existing access control systems rely on external tools for fraud detection, leading to redundancy, computational latency, and infeasibility when these tools are out-of-service, lacking granular control and scalability.
Innovation Solution
A service is configured with modular fraud detection rules organized into risk levels, sharing rule sets to reduce redundancy and computational load, allowing granular control and scalability by categorizing requests into risk levels and applying specific rule sets based on risk insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If external third-party tools are used for fraud detection, then comprehensive risk assessment capability is improved, but computational latency and system complexity increase
Solution Approach 1:
The patent extracts the essential fraud detection functionality from external third-party tools and implements it as internal rule sets within the service. The service maintains multiple rule sets that can be applied locally to assess fraud risk, eliminating the need to constantly query external tools while preserving comprehensive risk assessment capability.
Solution Approach 2:
The service pre-configures multiple rule sets with different fraud detection logic and thresholds before runtime. When a request arrives, the service can immediately apply the appropriate pre-loaded rule sets without waiting for external tool responses, significantly reducing computational latency while maintaining detection accuracy.
2Measurement precision
If multiple external tools are coordinated for access control, then detection accuracy is improved, but system reliability decreases when tools are inaccessible
Solution Approach 1:
The service implements multiple self-contained rule sets that can independently perform fraud detection. Each rule set represents a different detection approach, and the service can select and apply the most appropriate rule set based on the request context, ensuring both accurate detection and continuous operation even when certain detection methods are unavailable.
Solution Approach 2:
The service dynamically adjusts which rule sets to apply and what thresholds to use based on the specific request characteristics and current service conditions. This allows the service to maintain high detection accuracy by selecting the most appropriate rule set while ensuring reliability by having multiple options available locally without depending on external tool availability.
3Ease of operation
If blanket policies are applied to access control, then ease of operation is improved, but granular control capability deteriorates
Solution Approach 1:
The service segments fraud detection into multiple distinct rule sets, each targeting specific fraud patterns or risk categories. Each rule set can be independently configured and applied to different types of requests, enabling granular control over access decisions while maintaining ease of operation through modular rule management.
Solution Approach 2:
The service dynamically selects which rule sets to apply based on the specific request characteristics, user context, and risk assessment needs. This dynamic adaptation allows the service to provide granular control for high-risk requests while using simpler policies for low-risk requests, maintaining both ease of operation and adaptability.
4Measurement precision
If extensive rule sets are maintained for each risk level, then fraud detection precision is improved, but computational resource consumption increases
Solution Approach 1:
The service applies partial rule sets based on the assessed risk level of each request. For low-risk requests, only essential rule sets are applied, consuming minimal computational resources. For high-risk requests, the service activates more comprehensive rule sets to provide precise risk assessment, ensuring computational power is used efficiently while maintaining detection precision when needed.
Solution Approach 2:
The service organizes rule sets into hierarchical groups associated with different risk levels. This segmentation allows the service to apply only the necessary subset of rules based on the request's risk profile, reducing computational overhead for routine requests while maintaining comprehensive detection capability for suspicious activities.
Data Source
AI summary
Presented herein are system and methods for controlling access to services for processing requests. A server maintains rule sets defined for risk levels to control access to second services. Each of the risk levels defines a respective group of rule sets from the rule sets to apply. The server receives a request including authentication information of a transaction type for an end user device to access a second service. The server determines risk parameters and a challenge threshold. The server identifies a risk level for the request based on the risk parameters. The server selects a group of rule sets to apply for the identified risk level and applies the group of rule sets to the authentication information to perform at least one of a denial, allowance, or challenge of the request of the transaction type using the challenge threshold, for the end user device to access the second service.