EncGPT leverages large language models (LLMs) to create a dynamic encryption workflow that adapts to evolving security needs, marking a significant leap forward in cryptographic technology. EncGPT represents a significant advancement in communication encryption by introducing an agent-based workflow that dynamically generates encryption algorithms and keys. Enhanced Security: By dynamically generating encryption algorithms and keys, EncGPT eliminates vulnerabilities associated with static methods. The architecture ensures that plaintext only appears during user input and output stages, enhancing security by preventing “prompt contamination,” a phenomenon where previous encryption rules interfere with subsequent interactions. EncGPT takes this concept further by dynamically generating encryption rules and algorithms instead of relying on fixed methods. Researchers from Xi’an Jiaotong University have introduced EncGPT, an AI-powered multi-agent framework that dynamically generates encryption and decryption rules. This innovation addresses critical challenges in communication security, balancing cost-efficiency and high-level encryption reliability. Symmetric encryption, while fast, risks compromising security if keys are intercepted, whereas asymmetric encryption offers higher security but at the cost of increased computational complexity. This approach enhances encryption reliability and addresses communication security challenges in LLM-MA systems. EncGPT operates through three specialized agents: the Rule Agent, Encryption Agent, and Decryption Agent. Homomorphic Encryption: EncGPT supports operations on encrypted data without exposing sensitive information—a feature crucial for privacy-preserving applications like financial data processing. Cyber Security News is a Dedicated News Platform For Cyber News, Cyber Attack News, Hacking News & Vulnerability Analysis.
This Cyber News was published on cybersecuritynews.com. Publication date: Tue, 01 Apr 2025 15:45:04 +0000