王建华

职位：讲师

学历：博士研究生

学科：网络空间安全

研究领域或方向：联邦学习、人工智能安全

邮箱：wangjianhua02@tyut.edu.cn

职称：中级

个人简介
主要课程
主要成果

2024.7-至今：太原理工大学计算机科学与技术学院讲师
2020.9-2024.6：北京交通大学博士
2017.9-2020.6：太原理工大学硕士
2013.9-2017.6：太原理工大学学士
获2024年ACM太原分会新星奖，IEEE TDSC、TKDE、TNSE、IoTJ等SCI期刊审稿人，CWSN 2024组织委员会委员。
大数据安全
科研论文：
[1] Wang J, Chang X, Mišić J, et al. CRS-FL: Conditional Random Sampling for Communication-Efficient and Privacy-Preserving Federated Learning[J]. IEEE Transactions on Network and Service Management, 2024. (中科院2区)
[2] Wang J, Chang X, Mišić J, Mišić VB, et al. PA-iMFL: Communication-Efficient Privacy Amplification Method against Data Reconstruction Attack in Improved Multi-Layer Federated Learning [J]. IEEE Internet of Things Journal, 2024. (中科院2区TOP)
[3] Wang J, Chang X, Mišić J, Mišić VB, et al. PASS: A Parameter Audit-Based Secure and Fair Federated Learning Scheme Against Free-Rider Attack [J]. IEEE Internet of Things Journal, vol. 11, no. 1, pp. 1374-1384, 1 Jan.1, 2024. (中科院2区TOP)
[4] Wang J, Lei X, Liang M, et al. Towards Well-trained Model Robustness in Federated Learning: An Adversarial-Example-Generation-Efficiency Perspective [C]. IEEE International Conference on Communications (ICC), 2024. (CCF C)
[5] Wang J, Chang X, Rodrìguez R J, et al. Assessing anonymous and selfish free-rider attacks in federated learning[C]// IEEE Symposium on Computers and Communications (ISCC). IEEE, 2022: 1-6. (CCF C)
[6] Wang J, Chang X, Wang Y, et al. LSGAN-AT: enhancing malware detector robustness against adversarial examples[J]. Cybersecurity, 2021, 4(1): 1-15. (CCF C)
[7] Wang J, Chang X, Mišić J, et al. Mal-LSGAN: An Effective Adversarial Malware Example Generation Model[C]// IEEE Global Communications Conference (GlobeCom). IEEE, 2021: 1-6. (CCF C)
[8] Wang Y, Chang X, Zhu H, Wang J, et al. Towards Secure Runtime Customizable Trusted Execution Environment on FPGA-SoC [J]. IEEE Transactions on Computers, 2024. (CCF A)
[9] Gong Y, Chang X, Mišić J, Mišić VB, Wang J, et al. Practical Solutions in Fully Homomorphic Encryption - A Survey Analyzing Existing Acceleration Methods [J]. Cybersecurity, 2023. (CCF C)
[10] Wang W, Wang J, et al. Exploring best-matched embedding model and classifier for charging-pile fault diagnosis[J]. Cybersecurity, 2023, 6(1): 1-13. (CCF C)
[11] Wang Y, Liu J, Chang X, RJ Rodríguez, Wang J. DI-AA: An interpretable white-box attack for fooling deep neural networks[J]. Information Sciences, 2022, 610: 14–32. (中科院1区, CCF B)
[12] Wang Y, Liu J, Chang X, Wang J, et al. AB-FGSM: AdaBelief optimizer and FGSM-based approach to generate adversarial examples [J]. Journal of Information Security and Applications, 2022, 68: 103227. (中科院3区)
[13] Yao Y, Chang X, Wang J, et al. LPC: A lightweight pseudonym changing scheme with robust forward and backward secrecy for V2X [J]. Ad Hoc Networks, 2021, 123: 102695. (中科院3区)
[14] Yao Y, Zhao Z, Chang X, Wang J. A Novel Privacy-Preserving Neural Network Computing Approach for E-Health Information System[C]// IEEE International Conference on Communications (ICC). IEEE, 2021: 1-6. (CCF C会议)

发明专利：
[1] 常晓林，纪健全，姚英英，王建华。面向MEC环境的基于OAuth2.0的单点登录机制，2021.11.23，CN112822675B (已授权)。
[2] 陈永乐，马垚，杨玉丽，于丹，王建华。一种面向工控蜜罐的同源攻击分析方法，2019.12.27，ZL201911381260.7 (已授权)。

科研项目：
主持：
[1] 面向数据与模型安全的轻量化联邦遗忘方法研究，中央引导地方科技发展资金项目，2025.4-2027.12。
[2] 面向联邦学习搭便车攻击的评估及其防御策略研究，基本科研业务费研究生创新项目，2022-2024。

参与：
[1] 大规模联盟链共识算法效能分析及优化,国家自然科学基金面上，2023-2026。
[2] 面向多层域轨道交通“四网融合”的数据治理和可信交互关键技术研究（2），铁路总公司（原铁道部），2021-2023。
[3] 动静协同的恶意代码智能分析方法研究，国家自然科学基金“联合基金项目”，2019.1-2021.12。
[4] 航天信息隐私计算产品算法组件项目（子包-安全多方计算算法组件开发），横向，2023.11-2024.8。
[5] 规模化电动汽车与电网互动及充电安全防护技术研究，国网，横向，2020.9-2022-12。