Language Model Cyber Security System for Communication Authenticity
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Solution Overview
Problem
Existing cybersecurity systems struggle to detect malicious, deceptive, inauthentic, or untrustworthy electronic communications that appear legitimate and evade known security procedures.
Innovation Solution
A method and system that utilize a language model to analyze the intent of electronic communications by identifying relevant and irrelevant data, converting the relevant data into a prompt, executing the language model, and outputting a prediction on the communication's authenticity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional cybersecurity procedures are used to detect malicious electronic communications, then the system is easier to operate and requires less computational resources, but the detection accuracy decreases and malicious communications evade detection
Solution Approach 1:
The patent introduces an intermediary processing layer that extracts and analyzes specific features (sender information, recipient information, subject line, body text, links, attachments) separately before making a maliciousness determination. This intermediary feature extraction and analysis layer bridges the gap between simple traditional filters and complex AI models, improving detection accuracy while managing system complexity through structured feature processing.
Solution Approach 2:
The patent segments the electronic communication into distinct components (sender info, recipient info, subject, body, links, attachments) and processes each segment separately with appropriate analysis methods. This segmentation allows the system to apply specialized detection techniques to each component, improving overall detection accuracy while maintaining manageable system complexity through modular processing.
2Measurement precision
If comprehensive analysis of all communication content is performed, then detection accuracy improves, but processing time increases and productivity decreases
Solution Approach 1:
The patent applies partial analysis by focusing on the most critical features (sender verification, subject line analysis, body text scanning for malicious patterns, link validation) rather than exhaustively analyzing every element of the communication. This partial action approach maintains high detection accuracy for malicious content while improving processing throughput by avoiding unnecessary analysis of benign elements.
Solution Approach 2:
The patent applies different analysis depths to different parts of the communication based on their maliciousness indicators. High-priority sections (sender address, subject line, obvious malicious links) receive intensive analysis, while lower-priority sections receive lighter processing. This local quality differentiation improves overall detection accuracy while maintaining processing productivity through optimized resource allocation.
Data Source
AI summary
A method including receiving an electronic communication including content. The method also includes identifying, in the content, relevant data including a first portion of the content predetermined to be relevant to an evaluation of authenticity of the electronic communication and irrelevant data including a second portion of the content predetermined to be irrelevant to the evaluation. The method also includes converting the relevant data into a prompt for a language model. The method also includes executing the language model on the prompt. The method also includes outputting, by the language model, a prediction whether the electronic communication is at least one of malicious, deceptive, inauthentic, and untrustworthy.