An Explainable Agentic System for Detection of Conversational Scams with Summary-Based Memory
Following the rapid progress of generative Artificial Intelligence, there is a growing threat posed by conversational scams. These scams often span over multiple weeks or months, gradually build trust and request for money or sensitive information. Existing scam-detection systems mainly focus on isolated messages, which renders them inadequate against this evolving threat. This paper extends single-message phishing detection and presents an explainable agentic system for detecting sophisticated conversational scams. It also introduces ConScamBench-278, an initial public multi-category benchmar
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- LinkedLinked via arxiv author · 85%Ahmed Omar Salim Adnan →
“An Explainable Agentic System for Detection of Conversational Scams with Summary-Based Memory”
- LinkedLinked via arxiv author · 85%Yogananda Manjunath →
“An Explainable Agentic System for Detection of Conversational Scams with Summary-Based Memory”
- LinkedLinked via arxiv author · 85%Shivanjali Khare →
“An Explainable Agentic System for Detection of Conversational Scams with Summary-Based Memory”