Keyboard Anomaly Detection for Foreign Input Security
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Solution Overview
Problem
Existing systems fail to effectively detect and prevent unauthorized access attempts using foreign language keyboards, which are commonly employed by hackers to gain access to accounts, leading to potential data breaches and security vulnerabilities.
Innovation Solution
A keyboard detection system that utilizes a processor to identify anomalies in input data and determine correlations with inconsistent keyboard types through lookup tables or algorithms, activating fraud applications to limit or block access when anomalies are detected, thereby flagging potential hacking attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing systems use traditional access verification methods, then account access is granted based on credentials alone, but unauthorized access attempts using foreign keyboards cannot be detected
Solution Approach 1:
The system performs preliminary analysis of keyboard input patterns during normal authentication and ongoing usage. By establishing baseline typing characteristics beforehand and continuously monitoring deviations, the system detects foreign keyboard usage before it can cause significant security breaches, enhancing account security without requiring complex real-time intervention mechanisms
Solution Approach 2:
The patent introduces keyboard pattern analysis as an intermediary layer between traditional credential verification and account access. This intermediary mechanism analyzes typing rhythms, key press durations, and error patterns to detect foreign keyboard usage, adding security without fundamentally redesigning the entire access verification system
2Reliability
If the system monitors all input data for security analysis, then unauthorized access can be detected, but processing time and system resources increase
Solution Approach 1:
The system extracts only the most relevant features from input data for analysis, such as typing rhythm, error patterns, and key press durations. By focusing on these specific indicators rather than analyzing every single input character in detail, the system maintains high detection accuracy while significantly reducing processing time and computational resource requirements
Solution Approach 2:
The system applies partial monitoring by focusing analysis on critical authentication moments and high-risk input patterns. Rather than uniformly analyzing all input data with equal depth, the system intensifies analysis when anomalies are detected and reduces monitoring intensity during normal usage, optimizing the balance between detection accuracy and processing efficiency
Data Source
AI summary
A keyboard detection system, that includes a processor that operates to detect at least one anomaly in input data and determine a correlation between the at least one anomaly and a characteristic of an inconsistent keyboard type. The processor may operate to determine the correlation between the at least one anomaly and the characteristic of the inconsistent keyboard type based on a lookup table or algorithm.