Access Analysis System Using Behavioral Biometrics and Communication Patterns
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Solution Overview
Problem
Current access analysis systems face challenges in accurately distinguishing between legitimate and unauthorized users, as well as in determining normal versus abnormal communication, leading to potential misclassification.
Innovation Solution
An access analysis system comprising a first analysis unit for evaluating user validity based on terminal operation characteristics, a second analysis unit for assessing communication normality, and a determination unit that combines these results to accurately classify access validity using a matrix table approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If behavioral biometrics technique is used for user authentication, then spoofing detection capability is improved, but false recognition of legitimate users increases when terminal is used in unusual ways
Solution Approach 1:
The system divides access analysis into multiple independent evaluation dimensions: user validity evaluation (using behavioral biometrics) and communication normality evaluation (using communication pattern analysis). Each dimension operates independently and contributes to the final access validity determination, allowing the system to handle false positives by cross-referencing multiple criteria rather than relying on a single evaluation method
Solution Approach 2:
The system merges user validity evaluation results with communication normality evaluation results to determine final access validity. By combining multiple evaluation perspectives (user behavior patterns and communication patterns), the system achieves more accurate discrimination between legitimate and unauthorized access, reducing false recognition of legitimate users while maintaining spoofing detection capability
2Measurement precision
If UEBA technique is used for abnormal communication detection, then detection accuracy is improved, but false recognition of normal communication as abnormal increases
Solution Approach 1:
The system separates communication analysis into multiple evaluation criteria including communication pattern analysis, data volume analysis, and temporal pattern analysis. By segmenting the evaluation into distinct criteria, the system can apply UEBA techniques to detect abnormal patterns while using other criteria to verify and reduce false positives
Solution Approach 2:
The system uses feedback mechanisms where communication analysis results are continuously compared against established normal patterns and user behavior profiles. When communication patterns deviate from expected norms, the system triggers further investigation or blocks access, creating a feedback loop that refines detection accuracy over time while reducing false recognition of normal communication
Data Source
AI summary
An access analysis system includes: a first analysis unit that analyzes validity of a user based on a characteristic of an operation of a terminal by the user regarding access via a network; a second analysis unit that based on communication regarding the access, analyzes normality of the communication; and a determination unit that determines validity of the access based on an analysis result from the first analysis unit and an analysis result from the second analysis unit, thereby improving the accuracy of determining the validity of access via the network.