Auto-Click Detection via Hover and Fingerprint Analysis
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Solution Overview
Problem
Mobile computing devices are vulnerable to auto-click attacks, where malicious applications generate fake clicks to inflate ad revenue, leading to security vulnerabilities and resource misuse.
Innovation Solution
The system detects auto-clicks by analyzing click inputs in conjunction with hover and fingerprint events, determining if a click is legitimate based on temporal and spatial parameters, and performs security actions such as terminating malicious programs and notifying users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system monitors all click inputs to detect auto-clicks, then security detection capability is improved, but device processing overhead and energy consumption increase
Solution Approach 1:
The system performs preliminary analysis by checking for hover events before a click occurs. By detecting whether a finger hovered over the click location within a threshold time period before the click, the system can quickly identify suspicious clicks without performing more intensive analysis, thus reducing overall energy consumption while maintaining detection accuracy
Solution Approach 2:
The detection process is segmented into multiple stages: first checking for hover events (low computational cost), then analyzing fingerprint events (moderate cost), and only performing full click pattern analysis on suspicious cases. This segmentation allows the system to maintain high detection accuracy while minimizing average energy consumption by avoiding intensive analysis for all clicks
2Measurement precision
If the system analyzes multiple events (hover, fingerprint, click timing) to differentiate auto-clicks, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the event analysis into distinct, modular components: hover event detection module, fingerprint event detection module, and click event analysis module. Each module handles a specific type of event independently, making the overall system easier to implement and maintain while achieving high measurement precision through the combination of multiple event types
Solution Approach 2:
The system adds temporal and spatial dimensions to click detection by analyzing hover events (spatial proximity and temporal sequence) and fingerprint events (biometric identification). This multi-dimensional approach significantly improves measurement precision for determining click legitimacy without requiring complex changes to the core click handling logic
3Speed
If the system implements real-time analysis of finger proximity events, then auto-click detection speed is improved, but processing overhead increases
Solution Approach 1:
The system performs preliminary detection of hover events in real-time as the finger approaches the screen, before the actual click occurs. This preliminary action provides early warning of potential auto-clicks, enabling faster response time while keeping processing overhead manageable by only triggering full analysis when hover patterns are suspicious
Data Source
AI summary
The disclosed computer-implemented method for detecting and preventing auto-click attacks may include (1) detecting, by the computing device, a click input, (2) detecting, by the computing device, a finger in proximity to the computing device, (3) analyzing, by the computing device, at least one event associated with the finger, (4) determining, by the computing device, that the click input is an auto-click based on the analysis of the at least one event associated with the finger, and (5) performing a security action in response to determining that the click input is an auto-click. Various other methods, systems, and computer-readable media are also disclosed.