EncGPT: A Multi-Agent Workflow for Dynamic Encryption Algorithms

Communication encryption is crucial in computer technology, but existing algorithms struggle with balancing cost and security. We propose EncGPT, a multi-agent framework using large language models (LLM). It includes rule, encryption, and decryption agents that generate encryption rules and apply them dynamically. This approach addresses gaps in LLM-based multi-agent systems for communication security. We tested GPT-4o's rule generation and implemented a substitution encryption workflow with homomorphism preservation, achieving an average execution time of 15.99 seconds.

@article{li2025_2503.23138,
  title={ EncGPT: A Multi-Agent Workflow for Dynamic Encryption Algorithms },
  author={ Donghe Li and Zuchen Li and Ye Yang and Li Sun and Dou An and Qingyu Yang },
  journal={arXiv preprint arXiv:2503.23138},
  year={ 2025 }
}