Adaptive Authentication Risk Threshold Optimization
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Solution Overview
Problem
Previous adaptive authentication technologies face challenges in setting appropriate risk score thresholds, leading to inefficient resource use and performance issues due to the need for users to manually create policy rules, resulting in either increased false alarms or fraudulent requests being approved.
Innovation Solution
An adaptive authentication system automatically generates risk score thresholds using historical data to minimize business damages from false negatives and positives, optimizing resource allocation and dynamically adjusting thresholds based on current data and transaction values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If more requests are subjected to thorough authentication examination, then fraud risk is reduced, but false alarms increase and resource consumption increases
Solution Approach 1:
The system dynamically adjusts the risk score threshold parameter based on current fraud patterns, transaction volumes, and resource availability. By changing this critical parameter, the system optimizes the balance between detecting fraud and avoiding false alarms, ensuring thorough examination of high-risk requests while reducing unnecessary scrutiny of low-risk requests.
Solution Approach 2:
The authentication examination intensity is made dynamic rather than static. The system continuously adapts the level of scrutiny applied to requests based on real-time risk assessment, adjusting which requests receive thorough examination versus expedited processing, thereby optimizing resource allocation across varying workload conditions.
2Loss of energy
If less complex authentication techniques are used more frequently, then resource cost is reduced, but fraudulent requests may be approved
Solution Approach 1:
Different authentication techniques are applied locally to different requests based on their specific risk characteristics. Low-risk requests receive simple, low-cost authentication, while high-risk requests trigger more complex authentication processes. This localized approach ensures adequate fraud prevention for each request type without unnecessarily applying complex techniques to all requests.
Solution Approach 2:
The system applies authentication techniques proportionally to the risk level rather than using maximum security for all requests. Partial authentication (simplified processes) is applied to low-risk requests, while excessive or enhanced authentication is reserved for high-risk cases, optimizing the balance between security and resource efficiency.
3Ease of operation
If users manually create policy rules for each authentication request, then system control is improved, but system complexity increases and configuration difficulty increases
Solution Approach 1:
The system performs self-service by automatically generating and adjusting policy rules based on analyzed historical data and current risk patterns. Rather than requiring users to manually configure each policy rule, the system autonomously optimizes authentication requirements, reducing configuration complexity while maintaining effective control through data-driven decision-making.
Solution Approach 2:
The system incorporates feedback loops where outcomes of authentication decisions are analyzed and used to automatically refine policy rules. This continuous feedback mechanism enables the system to learn from past decisions and automatically adjust control parameters, reducing the need for manual configuration while improving system control over time.
4Ease of operation
If default or arbitrary risk threshold values are used, then configuration effort is reduced, but authentication performance suffers
Solution Approach 1:
The system performs preliminary analysis of historical authentication data and fraud patterns to pre-optimize risk threshold values before they are applied. By conducting this analysis in advance and automatically setting thresholds based on learned patterns, the system eliminates the need for users to manually configure thresholds while ensuring optimal authentication performance from the start.
Data Source
AI summary
A system for optimized configuration of an adaptive authentication service is disclosed that automatically generates one or more risk score thresholds. The system generates a risk score threshold or thresholds for an upcoming time period such that the business damages estimated to occur during the upcoming time period are minimized. The business damages estimated to occur during the upcoming time period may include business damages resulting from false negative authentication determinations, which incorrectly indicate that a fraudulent authentication request is legitimate, and false positive authentication determinations, which incorrectly indicate that a legitimate authentication request is fraudulent, and may be offset by the beneficial value of the enhancement to an organization's reputation resulting from true positive authentication determinations, which correctly indicate that an authentication request is fraudulent.