Xiuhua Lu | Blockchain | Best Researcher Award

Posted on by usudeeparya

Assoc. Prof. Dr. Xiuhua Lu | Blockchain | Best Researcher Award

Master Supervisor at Qufu Normal university, Chinađź“–

Xiuhua Lu, an Associate Professor at the School of Cyber Science and Engineering, Qufu Normal University, hails from Taian, Shandong, China. Born in October 1979, she has dedicated her career to advancing knowledge in lattice cryptography, blockchain, and federated learning. Her expertise in mathematics and information security has established her as a prominent figure in the field of cybersecurity and applied cryptography.

Profile

Scopus Profile

Orcid Profile

Education Background🎓

Xiuhua Lu holds a Bachelor of Science in Mathematics and Applied Mathematics from Shandong Normal University (1998–2002). She pursued a Master of Science in Applied Mathematics at Capital Normal University (2002–2005), deepening her analytical and mathematical prowess. Later, she earned a Doctor of Engineering in Information Security from Beijing University of Posts and Telecommunications (2011–2019), where she focused on advanced topics in cybersecurity and cryptography.

Professional Experience🌱

Xiuhua Lu began her academic journey as an Assistant Teacher at Langfang Normal University in 2005, progressing to Lecturer and subsequently Associate Professor during her 16-year tenure. Since January 2022, she has been serving as an Associate Professor at Qufu Normal University, where she continues to mentor students and lead research projects in the School of Cyber Science and Engineering.

Research Interests🔬

Xiuhua Lu’s research interests include lattice cryptography, blockchain technology, and federated learning. Her work focuses on developing secure and efficient solutions for modern challenges in data privacy, distributed systems, and cryptographic algorithms, positioning her as a key contributor to advancements in these areas.

Author Metrics

Xiuhua Lu has contributed significantly to her field through numerous research publications in lattice cryptography, blockchain applications, and federated learning. Her scholarly work is recognized for its innovative approach and practical applications, garnering citations and establishing her influence in cybersecurity and data privacy.

Publications Top Notes đź“„

1. Quantum-Resistant Identity-Based Signature with Message Recovery and Proxy Delegation

Authors: Lu, X., Wen, Q., Yin, W., Panaousis, E., Chen, J.
Journal: Symmetry, 2019, 11(2), 272
Abstract: This paper presents a quantum-resistant identity-based signature scheme that incorporates message recovery and proxy delegation capabilities. Leveraging lattice-based cryptography, the proposed method ensures robust security against quantum attacks while enhancing efficiency in identity-based systems.
Citations: 6

2. Message Integration Authentication in the Internet-of-Things via Lattice-Based Batch Signatures

Authors: Lu, X., Yin, W., Wen, Q., Chen, L., Chen, J.
Journal: Sensors (Switzerland), 2018, 18(11), 4056
Abstract: This study explores lattice-based batch signatures for message authentication in IoT systems. The proposed scheme effectively integrates and authenticates multiple messages simultaneously, addressing security and computational efficiency in resource-constrained IoT environments.
Citations: 4

3. A Lattice-Based Unordered Aggregate Signature Scheme Based on the Intersection Method

Authors: Lu, X., Yin, W., Wen, Q., Jin, Z., Li, W.
Journal: IEEE Access, 2018, 6, pp. 33986–33994
Abstract: This paper introduces a lattice-based unordered aggregate signature scheme utilizing the intersection method. The method enhances computational efficiency and scalability while ensuring strong security foundations, suitable for applications requiring high-performance aggregate signing.
Citations: 23

4. The Prediction of PM2.5 Value Based on ARMA and Improved BP Neural Network Model

Authors: Zhu, H., Lu, X.
Conference: Proceedings of the 2016 International Conference on Intelligent Networking and Collaborative Systems (IEEE INCoS), 2016, pp. 515–517
Abstract: This research proposes a hybrid model combining ARMA and an improved BP neural network for accurate PM2.5 value predictions. The model demonstrates improved forecasting accuracy, contributing to better environmental monitoring and pollution control strategies.
Citations: 46

5. A Lattice-Based Signcryption Scheme Without Trapdoors

Authors: Lu, X., Wen, Q., Wang, L., Du, J.
Journal: Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2016, 38(9), pp. 2287–2293
Abstract: The authors develop a lattice-based signcryption scheme that eliminates the need for trapdoors, enhancing both security and practical applicability. The scheme is tailored for secure communication in post-quantum scenarios, balancing confidentiality, authenticity, and efficiency.
Citations: 11

Conclusion

Dr. Xiuhua Lu is an outstanding candidate for the Best Researcher Award, owing to her groundbreaking work in quantum-resistant cryptography, blockchain technology, and federated learning. Her scholarly contributions are marked by innovation, practical relevance, and academic rigor, aligning seamlessly with the award’s objectives. Addressing areas like expanded collaboration, outreach, and leadership in large-scale projects could further elevate her already stellar profile.

Recommendation:

Awarding Dr. Lu this recognition would highlight her pivotal role in advancing cybersecurity and cryptographic research, inspiring further contributions in these critical fields.