Quantum Communication Filtering for AI Scam Detection
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Solution Overview
Problem
Electronic communications are vulnerable to scams and nefarious activities, particularly those leveraging artificial intelligence, which are difficult to detect, leading to an increase in undetected compromised communications.
Innovation Solution
A system utilizing quantum computing and AI to monitor and forecast compromised communications by generating predictive analytic profiles for senders based on their communication styles and applying dynamic quantum filters to authenticate and filter out suspicious messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If AI capabilities are improved to detect compromised communications, then detection accuracy is improved, but malicious actors can also leverage AI to create more sophisticated scams that are harder to detect
Solution Approach 1:
The patent introduces quantum computing as an intermediary layer between traditional AI detection systems and compromised communications. The quantum processor analyzes communication patterns and generates authenticity scores that supplement traditional AI detection, creating a multi-layered detection framework where quantum computing handles complex pattern recognition that classical AI struggles with
2Reliability
If quantum computing is used to monitor and detect compromised communications, then detection capability is improved, but system complexity increases
Solution Approach 1:
The patent segments the detection system into distinct functional modules: a quantum gateway with quantum processor for pattern analysis, a classical AI component for initial filtering, and a scoring system that combines both approaches. This segmentation allows each component to specialize in specific tasks, improving overall detection capability while managing complexity through modular architecture
Solution Approach 2:
The quantum gateway acts as an intermediary that bridges quantum computing capabilities and classical communication systems. It receives communications, performs quantum-based authenticity analysis, and outputs results that can be integrated with existing security infrastructure, thereby improving detection capability without requiring complete system replacement
3Reliability
If quantum signatures and dynamic filters are applied to authenticate messages, then security is improved, but processing time increases
Solution Approach 1:
The system performs preliminary quantum-based authenticity analysis on communications before they are fully processed and delivered. By generating authenticity scores in advance and filtering suspicious communications early in the workflow, the system improves security while minimizing impact on overall processing time through proactive rather than reactive detection
Data Source
AI summary
Methods, systems and apparatus for detecting, monitoring and forecasting for compromised electronic communications in an electronic communication system. Methods may include isolating, from a historical database, electronic communications associated with a plurality of senders into individual data capsules. Methods may include generating and storing a predictive analytic profile for each sender based on a communication style identified for each sender. Methods may include filtering out compromised electronic communications using a dynamic quantum filter, the dynamic quantum filter including a dynamic condition set. Filtering may include inserting a quantum signature into each incoming electronic communication. Methods may include retrieving the predictive analytic profile associated with the sender identified for each incoming electronic communication. Methods may include assigning condition values to each electronic communication based on comparing each electronic communication to a corresponding predictive analytic profile. Methods may include determining whether the assigned condition values conform with the dynamic condition set.