Publications

Published Research

Academic papers that form the theoretical and practical foundation of the NHP protocol.

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Network traffic control method of NHP based on deep reinforcement learning

Proposes an intelligent regulation method based on D3QN (Dueling Double Deep Q-Network) to address network traffic control challenges in NHP environments, achieving real-time perception and autonomous decision-making for throughput, latency, and packet loss optimization.

Qinglin Huang, Zhizhong Tan, Qiang Wang, Ziyi Jia and Benfeng Chen Scientific Reports (Nature) December 2025
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Research on Secure and Trusted Data Interaction Architecture for AI Agents

Explores secure data interaction architectures for AI agents, addressing the emerging security challenges of AI-driven systems.

Shuo Zhang, Rui Song, Benfeng Chen, et al. Computer Engineering and Applications August 2025
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DRL-AMIR: Intelligent Flow Scheduling for Software-Defined Zero Trust Networks

Applies deep reinforcement learning to intelligent flow scheduling in software-defined Zero Trust networks, optimizing NHP deployments.

Wenlong Ke, Zilong Li, Benfeng Chen, et al. CMC July 2025
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STALE: A Scalable and Secure Trans-Border Authentication Scheme Leveraging Email and ECDH Key Exchange

Presents a scalable trans-border authentication scheme using elliptic curve Diffie-Hellman key exchange, applicable to NHP cross-domain scenarios.

Jiexin Zheng, Mudi Xu, Benfeng Chen, et al. Electronics June 2025
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AHAC: Advanced Network-Hiding Access Control Framework

Introduces the AHAC framework for advanced network-hiding access control, providing the architectural foundation for the NHP protocol.

Mudi Xu, Benfeng Chen, et al. Applied Sciences Journal June 2024
Context

Related Research

Research that informs our understanding of AI-era security threats and solutions.

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From Naptime to Big Sleep: Using Large Language Models To Catch Vulnerabilities In Real-World Code

Demonstrates that LLMs can find real-world vulnerabilities in production code, highlighting the emerging threat of AI-powered security research.

Google Big Sleep Team Google Project Zero October 2024
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LLM Agents can Autonomously Exploit One-day Vulnerabilities

Shows that LLM agents can autonomously exploit known vulnerabilities without human intervention, dramatically reducing attack timelines.

Richard Fang, Rohan Bindu, et al. arXiv April 2024
Future Work

Research Directions

Open research questions and areas where we welcome academic collaboration.

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Post-Quantum Cryptography

Adapting NHP's cryptographic framework for quantum-resistant algorithms to ensure long-term security against quantum computers.

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AI-Resistant Protocols

Developing protocol extensions that remain secure against AI-powered attack tools and automated vulnerability discovery.

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Global Scale Deployment

Optimizing NHP for global-scale deployments with geographically distributed infrastructure and edge computing scenarios.

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Blockchain Integration

Exploring decentralized identity and access management using blockchain technology combined with NHP's hiding capabilities.

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Formal Verification

Applying formal methods to mathematically prove the security properties of the NHP protocol implementation.

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IoT & Industrial Systems

Adapting NHP for resource-constrained IoT devices and critical infrastructure protection in industrial environments.

Collaboration

Partner with Us

We actively collaborate with universities and research institutions on cybersecurity protocol research. If you're interested in exploring Zero Trust networking, cryptographic protocols, or AI-era security challenges, we'd love to hear from you.

Collaboration Opportunities

  • Joint research projects and publications
  • Graduate student thesis supervision
  • Security audits and formal verification
  • Protocol extension design
Contact Research Team

Acknowledgments

We gratefully acknowledge the contributions of our research partners:

  • 🏛️
    Cloud Security Alliance (CSA)

    Zero Trust Working Group collaboration

  • 🏛️
    China Computer Federation (CCF)

    Collaborative research support

  • 🌐
    OpenNHP Community

    Testing, feedback, and implementation

Advance Zero Trust Research

Join our research community and help shape the future of network security.