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Publication at IEEE CAI 2025: SocialCipher Framework

·188 words·1 min·
Research Publications Research AI/ML Publication Threat Detection IEEE
Aman Thanvi
Author
Aman Thanvi
Cybersecurity Specialist with a Master of Engineering in Cybersecurity from the University of Maryland, College Park. Over six years of progressive cybersecurity experience within federal government and the private sector.
Table of Contents

SocialCipher: A Multimodal Framework for Proactive Threat Detection with SentIntel
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I’m pleased to announce that our paper has been accepted and presented at the IEEE Conference on Artificial Intelligence (CAI) 2025 in Santa Clara, California.

Research Overview
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The research, conducted in collaboration with MIT Lincoln Laboratory, introduces a multimodal framework for proactive cyber threat detection using sentiment analysis and Large Language Models (LLMs). The work addresses the challenge of identifying potential threats during their planning stages rather than after execution.

Technical Contribution
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SocialCipher presents a novel approach combining:

  • Multimodal data analysis across multiple threat intelligence sources
  • Sentiment Intelligence (SentIntel) engine for pattern recognition
  • LLM integration for contextual understanding of threat indicators
  • Real-time processing capabilities for actionable intelligence

Conference Presentation
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The paper was presented at IEEE CAI 2025, where it received positive feedback from the research community. The conference provided valuable opportunities for discussion with other researchers working on AI applications in cybersecurity.

Acknowledgments
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This research was made possible through collaboration with MIT Lincoln Laboratory and the support of my co-authors and mentors.

The full paper will be available in the IEEE Digital Library.