研究方向

移动边缘计算安全、可信计算、云安全审计和信息隐藏检测等方面的理论与应用研究工作。

个人简介

博士，副教授，硕士生导师。IEEE IEEE高级会员、中国密码学会会员。2014年在北京邮电大学获得计算机科学与技术博士学位；2013.10-2014.10受国家留学基金委资助到Essex大学联合博士培养；2014.10-2016.10在清华大学电子工程系从事博士后研究工作；2016.10-现在，北京工业大学计算机学院从事教学科研工作。

课程教学

本科生教学：学术写作课程、学术前沿课程

科研项目

1. 2021-2023，基于强化学习的雾计算无线通信安全技术研究,北京市自然科学基金-面上项目,负责人

2. 2021-2022，基于虚拟化的可信计算安全技术与实现,教育部—中国移动科研基金项目,负责人

3. 2019-2021，云存储数据机密性公开审计模型与方法,国家自然科学基金-青年项目，负责人

4. 2018-2021,移动互联网数据防护技术试点示范,科技部国家重点研发计划-子课题，负责人

5. 2019-2020,基于区块链的云数据安全融合机制与方法，北京市教委项目-科技计划项目,负责人

6. 2018-2020,面向5G增强/虚拟现实及通信与计算融合的移动边缘计算基础理论与关键技术,北京市自然科学基金-联合重点项目子课题,负责人

7.  2019-2020，基于arm处理器的嵌入式可信计算平台研发，企业合作项目，负责人

荣誉和获奖

“电力用户大数据智能画像技术及应用”，2017.10，获中国人工智能学会科学技术奖一等奖。

主要论文论著

[1] Yongjie Yang, Shanshan Tu, Raja Hashim Ali, Hisham Alasmary, Muhammad Waqas, Muhammad Nouman Amjad. Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism. CMC-Computers, Materials & Continua, 2023, 74(1): 801-815.

[2] Muhammad Waqas, Shanshan Tu∗, Jialin Wan, Talha Mir, Hisham Alasmary, Ghulam Abbas. Defense scheme against advanced persistent threats in mobile fog computing security. Computer Networks, 2023, 221: 109519.

[3] Suleman Munawar, Zaiwar Ali, Muhammad Waqas, Shanshan Tu, Syed Ali Hassan, Ghulam Abbas. Cooperative Computational Offloading in Mobile Edge Computing for Vehicles: A Model-Based DNN Approach. IEEE Transactions on Vehicular Technology, 2023, 72(3): 3376-3391.

[4] Shanshan Tu, Haoyu Yu, Akhtar Badshah, Muhammad Waqas, Zahid Halim, Iftekhar Ahmad. Secure Internet of Vehicles (IoV) with Decentralized Consensus Blockchain Mechanism. IEEE Transactions on Vehicular Technology, 2023, 1-10.

[5] Bei Gong, Guiping Zheng, Muhammad Waqas, Shanshan Tu, Sheng Chen. LCDMA: Lightweight Cross-domain Mutual Identity Authentication Scheme for Internet of Things. IEEE Internet of Things Journal, 2023, 1-1.

[6] Jiangjiang Zhang, Zhenhu Ning, Raja Hashim Ali, Muhammad Waqas, Shanshan Tu, Iftekhar Ahmad. A Many-objective Ensemble Optimization Algorithm for the Edge Cloud Resource Scheduling Problem. IEEE Transactions on Mobile Computing, 2023, 1-18.

[7] Jiangjiang Zhang, Bei Gong, Muhammad Waqas, Shanshan Tu, Zhu Han. A Hybrid Many-Objective Optimization Algorithm for Task Offloading and Resource Allocation in Multi-Server Mobile Edge Computing Networks. IEEE Transactions on Services Computing, 2023, 1-14.

[8] Haoyu Yu, Farman Ali, Shanshan Tu*, Hanen M. Karamti, Ammar Armghan, Fazal Muhammad, Fayadh Alenezi, Khurram Hameed, Nauman Ahmad. Deducing of Optical and Electronic Domains Based Distortions in Radio over Fiber Network. Applied Sciences, 2022, 12(2): 753.

[9] Muhammad Noman, Shanshan Tu*, Shahab Ahmad, Fahad Ullah Zafar, Haseeb Ahmad Khan, Sadaqat Ur Rehman, Muhammad Waqas, Adnan Daud Khan, Obaid ur Rehman. Assessing the reliability and degradation of 10-35 years field-aged PV modules. PLoS One, 2022, 17(1): e0261066.

[10] Xiaoping Wang，Shanshan Tu*，Wei Zhao，Chengjie Shi. A novel energy-based online sequential extreme learning machine to detect anomalies over real-time data streams. Neural Computing and Applications, 2022, 34(2): 823–831

[11] Shanshan Tu, Muhammad Waqas, Sadaqat Ur Rehman, Talha Mir, Zahid Halim, Iftekhar Ahmad. Social Phenomena and Fog Computing Networks: A Novel Perspective for Future Networks. IEEE Transactions on Computational Social Systems, 2022, 9(1): 32-44.

[12] Muhammad Waqas, Shehr Bano, Fatima Hassan, Shanshan Tu, Ghulam Abbas, Ziaul Haq Abbas. Physical Layer Authentication Using Ensemble Learning Technique in Wireless Communications. CMC-Computers, Materials & Continua, 2022, 73(3): 4489-4499.

[13] Chao Fang, Hang Xu, Yihui Yang, Zhaoming Hu, Shanshan Tu, Kaoru Ota, Zheng Yang, Mianxiong Dong, Zhu Han, F. Richard Yu, Yunjie Liu. Deep-Reinforcement-Learning Based Resource Allocation for Content Distribution in Fog Radio Access Networks. IEEE Internet of Things Journal, 2022, 9(18): 16874-16883. WOS:000884575200012.

[14] Muhammad Waqas, Shanshan Tu*, Zahid Halim, Sadaqat Ur Rehman, Ghulam Abbas, Ziaul Haq Abbas. The role of artificial intelligence and machine learning in wireless networks security: principle, practice and challenges. Artificial Intelligence Review, 2022 55(7): 5215–5261.