Our cybersecurity research program is dedicated to advancing techniques, algorithms, and knowledge essential for protecting systems and data against threats. It delves into emerging threats such as data/model poisoning, eavesdropping, and privacy leakage while also bolstering intrusion detection systems. Through collaborative efforts, our researchers strive to develop robust cybersecurity solutions that protect privacy and ensure the integrity of digital assets. This program aims to strengthen cyber defenses in an ever-evolving technological landscape.
Academics and Coursework
In addition to broader requirements for a CS undergraduate or graduate degree, students may specialize their education around Cybersecurity research topics via these undergraduate and graduate level courses:
Undergraduate Courses
| CSC 415 | Operating System Principles |
| CSC 645 | Computer Networks |
| CSC 652 | Introduction to Security and Data Privacy |
| CSC 653 | Network Security |
| CSC 675 | Introduction to Database Systems |
Graduate Courses
| CSC 845 | Advanced Computer Networks |
| CSC 852 | Introduction to Security and Data Privacy |
| CSC 853 | Network Security |
| CSC 890 | Graduate Seminar - Machine Learning for Cybersecurity |
| CSC 895 | Applied Research Project |
| CSC 897 | Research |
| CSC 898 | Master's Thesis |
Faculty and Focus Areas
Publications and Reports
S. Jiang, J. Li, X. Zhang, H. Yue, H. Wu and Y. Zhou, "Secure and Privacy-Preserving Energy Trading with Demand Response Assistance Based on Blockchain," in IEEE Transactions on Network Science and Engineering, doi: 10.1109/TNSE.2023.3321754. (2023)
X. Zhang, J. Wang, H. Zhang, L. Li, M. Pan and Z. Han, "Data-Driven Transportation Network Company Vehicle Scheduling With Users’ Location Differential Privacy Preservation," in IEEE Transactions on Mobile Computing, vol. 22, no. 2, pp. 813-823, 1 Feb. 2023, doi: 10.1109/TMC.2021.3091148.
L. Li et al., "Privacy Preserving Participant Recruitment for Coverage Maximization in Location Aware Mobile Crowdsensing," in IEEE Transactions on Mobile Computing, vol. 21, no. 9, pp. 3250-3262, 1 Sept. 2022, doi: 10.1109/TMC.2021.3050147.
Q. Wang, H. Sun, R. Q. Hu and A. Bhuyan, "When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges," in IEEE Open Journal of the Communications Society, vol. 3, pp. 176-208, 2022, doi: 10.1109/OJCOMS.2022.3146364.
X. Zhang et al., "Data-Driven Caching With Users’ Content Preference Privacy in Information-Centric Networks," in IEEE Transactions on Wireless Communications, vol. 20, no. 9, pp. 5744-5753, Sept. 2021, doi: 10.1109/TWC.2021.3069763.
Q. Wang, F. Zhou, R. Q. Hu and Y. Qian, "Energy Efficient Robust Beamforming and Cooperative Jamming Design for IRS-Assisted MISO Networks," in IEEE Transactions on Wireless Communications, vol. 20, no. 4, pp. 2592-2607, April 2021, doi: 10.1109/TWC.2020.3043325.
S. Jiang, X. Zhang, J. Li, H. Yue and Y. Zhou, "Secure and Privacy-preserving Energy Trading Scheme based on Blockchain," GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020, pp. 1-6, doi: 10.1109/GLOBECOM42002.2020.9348246.
Ding, Jiahao, et al. "Towards plausible differentially private ADMM based distributed machine learning." Proceedings of the 29th ACM International Conference on Information & Knowledge Management. 2020.
R. Chen, X. Zhang, J. Wang, Q. Cui, W. Xu and M. Pan, "Data-Driven Small Cell Planning for Traffic Offloading with Users’ Differential Privacy," ICC 2020 - 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020, pp. 1-6, doi: 10.1109/ICC40277.2020.9149254.
Q. Wang, H. Hu, H. sun and R. Q. Hu, "Secure and Energy-Efficient Offloading and Resource Allocation in a NOMA-Based MEC Network," 2020 IEEE/ACM Symposium on Edge Computing (SEC), San Jose, CA, USA, 2020, pp. 420-424, doi: 10.1109/SEC50012.2020.00063.
Grants and Awards
Uncover the Ghost: Deep Learning based Spammer Detection on Twitter, Principal Investigator (Hao Yue), $10,000, SFSU ORSP Small Grant, 08/16/2018-08/15/2019.
Privacy-Preserving Medical Data Access in Future eHealth Systems, Principal Investigator (Hao Yue), $5,000, SFSU Center for Computing in Life Sciences (CCLS), 02/01/2016-01/31/2017.