Voice Phishing Detection via Conversation Pattern Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Voice phishing, or 'vishing,' poses challenges for legal authorities in monitoring and tracing activities, as well as notifying the public, due to its difficulty in detection and tracing.
Innovation Solution
A question answer system monitors voice conversations, parses them into information phrases, constructs conversation patterns, and identifies deceptive properties by analyzing against domain-based patterns, sending alerts to entities involved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If voice phishing activities are conducted using VoIP systems to mask caller identity, then the difficulty of tracing and monitoring the activity increases, but the ability to capitalize on victims remains effective
Solution Approach 1:
The patent introduces an intermediary monitoring system that sits between the voice phishing activity and the victims. This system analyzes conversation patterns in real-time, parsing speech into information phrases and comparing them against domain-based patterns to detect deceptive properties without exposing the victim to the actual phishing source. The intermediary enables detection and alerting while maintaining the ability to trace and monitor previously undetectable voice phishing activities.
2Adaptability or versatility
If traditional email phishing methods are used, then the method is well-established and effective, but voice phishing provides a more direct and personal attack vector
Solution Approach 1:
The patent replaces traditional mechanical detection methods with cognitive analysis. Instead of relying on signature-based detection or manual analysis, the system uses natural language processing to parse speech into information phrases, construct conversation patterns, and cognitively evaluate them against domain knowledge. This substitution enables detection of voice phishing's adaptive and versatile nature by understanding the semantic content and structure of conversations rather than just matching predefined patterns.
3Measurement precision
If a monitoring system analyzes conversation patterns in real-time, then detection accuracy improves, but system complexity and processing requirements increase
Solution Approach 1:
The patent segments the complex task of voice phishing detection into distinct modular components: (1) parsing speech into information phrases, (2) constructing conversation patterns from sequences of phrases, (3) evaluating patterns against domain-based conversation patterns, and (4) generating alerts. Each module handles a specific aspect of the analysis, reducing overall system complexity while maintaining high detection accuracy through systematic breakdown of the monitoring process.
Data Source
AI summary
An approach is provided in which a question answer system monitors a voice conversation between a first entity and a second entity. During the conversation, the question answer system parses the conversation into information phrases, and constructs the information phrases into a current conversation pattern. The question answer system identifies deceptive conversation properties of the current conversation by analyzing the current conversation pattern against domain-based conversation patterns. The question answer system, in turn, sends an alert message to the first entity to notify the first entity of the identified deceptive conversation properties.