Prof. Dr. Hongtao Li is a distinguished researcher specializing in cryptography and its applications, IoT security, large model security, and AI security. He serves as a council member of the Shanxi Computer Society and has been recognized under the “Sanjin Talent” Support Program in Shanxi Province. His research contributions encompass privacy-preserving mechanisms for big data, federated learning, blockchain-based auditing, and secure data collection for smart cities and IoT systems. He has led multiple high-profile projects, including a National Natural Science Foundation of China Youth Project on big data security and privacy protection, and several provincial-level initiatives focused on IoT security, medical big data protection, and cyberspace education reform. Prof. Li holds two authorized patents for computer network security and information security devices, reflecting his strong applied research impact. He has published over 50 papers in high-impact journals, addressing differential privacy, location privacy, blockchain protocols, and privacy-preserving schemes for digital communities and healthcare systems. His work demonstrates a consistent focus on safeguarding data and enhancing security frameworks in complex networked environments. With an h-index of 11, 328 citations by 314 documents, and 30 scholarly publications, Prof. Li’s research has significantly influenced both theoretical and applied aspects of cybersecurity, particularly in IoT and large-scale data environments, positioning him as a leading figure in advancing secure and privacy-preserving technologies in China and internationally.
Profile: Scopus
Featured publications
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Wang, J., Zhang, Z. J., Tian, J., & Li, H. T. (2024). Local differential privacy federated learning based on heterogeneous data multi-privacy mechanism. Computer Networks, 254, 110822.
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Li, H. T., Ma, J. F., & Fu, S. (2015). A privacy-preserving data collection model for digital community. Science China Information Sciences, 58(3), 1–16.
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Li, H. T., Guo, F., & Wang, L., et al. (2021). A blockchain-based public auditing protocol with self-certified public keys for cloud data. Security and Communication Networks, 2021(3), 1–10.
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Li, H. T., Wang, Y., & Guo, F., et al. (2021). Differential privacy location protection method based on the Markov model. Wireless Communications and Mobile Computing, 2021, 1–10.
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Li, H. T., Xue, X., Li, Z., et al. (2021). Location privacy protection scheme for LBS in IoT. Wireless Communications and Mobile Computing, 2021, 1–18.