Ji, Shouling

Privacy Risks of General-Purpose Language Models

Pan, X., Zhang, M., Ji, S., & Yang, M. (2020) · 2020 IEEE Symposium on Security and Privacy (SP)

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 188

DEEPSEC: A Uniform Platform for Security Analysis of Deep Learning Model

Ling, X., Ji, S., Zou, J., Wang, J., Wu, C., Li, B., & Wang, T. (2019) · 2019 IEEE Symposium on Security and Privacy (SP)

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 152

LLMs Cannot Reliably Judge (Yet?): A Comprehensive Assessment on the Robustness of LLM-as-a-Judge

Li, S., Xu, C., Wang, J., Gong, X., Chen, C., Zhang, J., Wang, J., Lam, K.-Y., & Ji, S. (2025) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 40

Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era

Li, C., Wang, L., Ji, S., Zhang, X., Xi, Z., Guo, S., & Wang, T. (2022) · arXiv

Biometric Identification and SecurityDigital Media Forensic Detection

Cited by 14

DEEPFAKER: A Unified Evaluation Platform for Facial Deepfake and Detection Models

Wang, L., Meng, X., Li, D., Zhang, X., Ji, S., & Guo, S. (2024) · ACM Transactions on Privacy and Security

Digital Media Forensic DetectionBiometric Identification and Security

Cited by 11

Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents

Gan, Y., Yang, Y., Ma, Z., He, P., Zeng, R., Wang, Y., Li, Q., Zhou, C., Li, S., Wang, T., et al. (2024) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 8

Incorporating Gradients to Rules: Toward Online, Adaptive Provenance-Based Intrusion Detection

Li, Z., Wang, L., Wang, Z., Shen, X., Xu, H., Chen, Y., & Ji, S. (2026) · IEEE Transactions on Dependable and Secure Computing

Network Security and Intrusion DetectionSecurity and Verification in Computing

Cited by 2