UI Interaction Anomaly Detection for Human-Bot Input Separation
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Solution Overview
Problem
Existing systems struggle to effectively distinguish between human and automated input in user interfaces, leading to potential security breaches and fraudulent activities.
Innovation Solution
An anomalous activity detection system analyzes interaction locations on user interfaces, comparing them to baseline data to identify deviations that indicate automated input, preventing unauthorized access and filtering out anomalous interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional input detection methods are used, then the system is simple to operate, but it cannot effectively distinguish between human and automated input
Solution Approach 1:
The patent segments the input detection process into multiple independent analysis dimensions: interaction location distribution, interaction timing patterns, interaction sequence validation, and device fingerprinting. Each dimension processes specific features independently and contributes to the overall authentication decision, enabling comprehensive detection without requiring a monolithic complex system
Solution Approach 2:
The patent introduces an intermediary analysis layer that sits between raw input detection and authentication decisions. This intermediary layer analyzes interaction patterns, locations, and timing to generate confidence scores, which then inform the final authentication decision. This mediator enables accurate distinction between human and automated input while maintaining a clear separation of concerns in the system architecture
2Reliability
If automated systems are allowed to access user interfaces, then processing efficiency increases, but security risks and fraudulent activities increase
Solution Approach 1:
The patent performs preliminary analysis of interaction patterns, locations, and device characteristics before granting full access to the system. By pre-evaluating these factors and establishing baseline behavior, the system can quickly authenticate legitimate users while blocking automated attacks, thus maintaining both security and processing efficiency
Solution Approach 2:
The patent dynamically adjusts detection sensitivity and analysis depth based on the evaluated risk level. For low-risk interactions from authenticated devices, the system processes requests efficiently with minimal analysis. For suspicious patterns, the system increases analysis depth and applies stricter validation, optimizing the balance between security and productivity
3Measurement precision
If interaction location analysis is performed, then automated input detection improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies partial analysis to interaction locations by focusing on key distribution patterns and critical interaction zones rather than analyzing every single coordinate point in detail. This selective approach maintains high detection accuracy for automated vs. human input while significantly reducing the computational time and resources required
Data Source
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AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting anomalous user interface interactions. One of the methods includes receiving, for a user interface element, interaction locations that indicate where interactions with the user interface element occurred when the user interface element was provided on behalf of a first system; determining a difference between (i) a first distribution of the interaction locations for the user interface element when the user interface element was provided on behalf of the first system and (ii) a second distribution of the interaction locations for the user interface element when the user interface element was provided on behalf of a second system; classifying the first distribution of the interaction locations as anomalous in response to the difference not satisfying a condition; and preventing the first system from accessing another system to which the first system was trying to gain access.