Entity Interaction Risk Analysis System Using Segmented Modules
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Solution Overview
Problem
Existing technologies face challenges in effectively determining the extent of security risk associated with entity interactions, particularly in verifying the identity of entities and distinguishing between sanctioned and non-sanctioned interactions.
Innovation Solution
A method and system for performing an entity interaction risk analysis operation, which involves monitoring entities, identifying interactions, analyzing these interactions, determining if they are non-sanctioned, and performing appropriate security operations in response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entity interaction monitoring and analysis is performed to determine security risk, then security risk assessment capability is improved, but system complexity increases
Solution Approach 1:
The system segments the security risk assessment process into distinct functional modules: entity monitoring module, interaction identification module, analysis module, and security operation module. Each module handles a specific aspect of the risk assessment process, making the overall complex system more manageable and maintainable while improving reliability through specialized processing at each stage.
Solution Approach 2:
The patent introduces an intermediary analysis module that sits between the monitoring/identification components and the security operation components. This intermediary layer processes interaction data, determines sanctioned vs. non-sanctioned status, and decides on appropriate security operations, thereby mediating the complexity between data collection and response execution.
2Reliability
If real-time entity identity resolution is performed to prevent unauthorized access, then security response time is improved, but processing speed requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing entity profiles, interaction histories, and sanctioned interaction frameworks before actual security incidents occur. When an interaction is detected, the system can quickly compare it against pre-existing data structures and decision trees, enabling real-time responses without requiring complex real-time analysis from scratch.
Solution Approach 2:
The system implements feedback mechanisms where interaction outcomes and entity behavior patterns are continuously fed back into the monitoring and analysis components. This enables the system to learn from past interactions and improve its real-time decision-making capability, gradually reducing processing time requirements as the system becomes more efficient at pattern recognition.
3Measurement precision
If comprehensive interaction analysis is performed to distinguish sanctioned and non-sanctioned interactions, then security accuracy is improved, but data processing volume increases
Solution Approach 1:
The system applies local quality by tailoring the depth and scope of interaction analysis to the specific context and risk level of each interaction. High-risk interactions receive comprehensive analysis with multiple verification steps, while low-risk interactions undergo simplified processing. This selective approach maintains high security accuracy for critical cases while reducing overall data processing volume.
Solution Approach 2:
The system dynamically changes analysis parameters based on interaction characteristics, entity risk profiles, and contextual factors. By adjusting the number of verification steps, depth of analysis, and types of data consulted based on the specific interaction being evaluated, the system achieves high accuracy without uniformly processing all interactions at maximum depth, thereby reducing overall data processing volume.
Data Source
AI summary
A system, method, and computer-readable medium for performing entity interaction risk analysis operation. The entity interaction risk analysis operation includes: monitoring an entity, the monitoring observing an electronically-observable data source; identifying an interaction between the entity and another entity based upon the monitoring; analyzing the interaction between the entity and the another entity; determining whether the interaction between the entity and the another entity is non-sanctioned; and, performing a security operation in response to the analyzing the interaction and the determining whether the interaction is non-sanctioned.