大数据和云计算安全组主要关注大数据和云计算环境下的安全问题，包括数据隐私保护、访问控制、加密技术、安全认证和审计、威胁检测与防范等方面的研究。主要进行面向大数据和云计算安全的安全分析方法、辅助工具和自动化攻防技术的研究。本方向的研究成果包括大数据和云计算安全分析方法改进与工具实现、安全漏洞的发现与提交。
近几年发表的部分论文
[1] Zhang, Mingyu, Wenqiang Ge, Ruichun Tang, and Peishun Liu. Hard Disk Failure Prediction Based on Blending Ensemble Learning. Applied Sciences 13, no. 5 (2023): 3288.
[2] Liu, Peishun, Bing Tian, Xiaobao Liu, Shijing Gu, Li Yan, Leon Bullock, Chao Ma, Yin Liu, and Wenbin Zhang. Construction of Power Fault Knowledge Graph Based on Deep Learning. Applied Sciences 12, no. 14 (2022): 6993.
[3] Shao, Yangyi, Wenbin Zhang, Peishun Liu, Ren Huyue, Ruichun Tang, Qilin Yin, and Qi Li. Log Anomaly Detection method based on BERT model optimization. In 2022 7th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA), pp. 161-166. IEEE, 2022.
[4] Gu, Shijing, Yuchun Chu, Wenbin Zhang, Peishun Liu, Qilin Yin, and Qi Li. Research on System Log Anomaly Detection Combining Two-way Slice GRU and GA-Attention Mechanism. In 2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD), pp. 577-583. IEEE, 2021.
[5] Lin, Xi-Jun, Qihui Wang, Lin Sun, Zhen Yan, and Peishun Liu. Security analysis of the first certificateless proxy signature scheme against malicious-but-passive KGC attacks. The Computer Journal 64, no. 4 (2021): 653-660.