| Textbugger: Generating adversarial text against real-world applications J Li, S Ji, T Du, B Li, T Wang arXiv preprint arXiv:1812.05271, 2018 | 706 | 2018 |
| {CoVisor}: a compositional hypervisor for {software-defined} networks X Jin, J Gossels, J Rexford, D Walker 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2015 | 347* | 2015 |
| Dual encoding for zero-example video retrieval J Dong, X Li, C Xu, S Ji, Y He, G Yang, X Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 293 | 2019 |
| {MOPT}: Optimized mutation scheduling for fuzzers C Lyu, S Ji, C Zhang, Y Li, WH Lee, Y Song, R Beyah 28th USENIX Security Symposium (USENIX Security 19), 1949-1966, 2019 | 289 | 2019 |
| Temporal multi-graph convolutional network for traffic flow prediction M Lv, Z Hong, L Chen, T Chen, T Zhu, S Ji IEEE Transactions on Intelligent Transportation Systems 22 (6), 3337-3348, 2020 | 231 | 2020 |
| Model-reuse attacks on deep learning systems Y Ji, X Zhang, S Ji, X Luo, T Wang Proceedings of the 2018 ACM SIGSAC conference on computer and communications …, 2018 | 186 | 2018 |
| Interpretable deep learning under fire X Zhang, N Wang, H Shen, S Ji, X Luo, T Wang 29th {USENIX} security symposium ({USENIX} security 20), 2020 | 183 | 2020 |
| Privacy risks of general-purpose language models X Pan, M Zhang, S Ji, M Yang 2020 IEEE Symposium on Security and Privacy (SP), 1314-1331, 2020 | 178 | 2020 |
| Certchain: Public and efficient certificate audit based on blockchain for tls connections J Chen, S Yao, Q Yuan, K He, S Ji, R Du IEEE INFOCOM 2018-IEEE conference on computer communications, 2060-2068, 2018 | 165 | 2018 |
| Differentially private releasing via deep generative model (technical report) X Zhang, S Ji, T Wang arXiv preprint arXiv:1801.01594, 2018 | 165 | 2018 |
| Deepsec: A uniform platform for security analysis of deep learning model X Ling, S Ji, J Zou, J Wang, C Wu, B Li, T Wang 2019 IEEE Symposium on Security and Privacy (SP), 673-690, 2019 | 156 | 2019 |
| Label inference attacks against vertical federated learning C Fu, X Zhang, S Ji, J Chen, J Wu, S Guo, J Zhou, AX Liu, T Wang 31st USENIX security symposium (USENIX Security 22), 1397-1414, 2022 | 151 | 2022 |
| Graph data anonymization, de-anonymization attacks, and de-anonymizability quantification: A survey S Ji, P Mittal, R Beyah IEEE Communications Surveys & Tutorials 19 (2), 1305-1326, 2016 | 149 | 2016 |
| Graph backdoor Z Xi, R Pang, S Ji, T Wang 30th USENIX security symposium (USENIX Security 21), 1523-1540, 2021 | 142 | 2021 |
| Structural data de-anonymization: Quantification, practice, and implications S Ji, W Li, M Srivatsa, R Beyah Proceedings of the 2014 ACM SIGSAC conference on computer and communications …, 2014 | 137 | 2014 |
| Sirenattack: Generating adversarial audio for end-to-end acoustic systems T Du, S Ji, J Li, Q Gu, T Wang, R Beyah Proceedings of the 15th ACM Asia conference on computer and communications …, 2020 | 135 | 2020 |
| Deep dual consecutive network for human pose estimation Z Liu, H Chen, R Feng, S Wu, S Ji, B Yang, X Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 124 | 2021 |
| Trojaning language models for fun and profit X Zhang, Z Zhang, S Ji, T Wang 2021 IEEE European Symposium on Security and Privacy (EuroS&P), 179-197, 2021 | 122 | 2021 |
| On your social network de-anonymizablity: Quantification and large scale evaluation with seed knowledge. S Ji, W Li, NZ Gong, P Mittal, RA Beyah NDSS, 2015 | 113 | 2015 |
| VulSniper: Focus Your Attention to Shoot Fine-Grained Vulnerabilities. X Duan, J Wu, S Ji, Z Rui, T Luo, M Yang, Y Wu IJCAI, 4665-4671, 2019 | 112 | 2019 |
Raheem BeyahDean and Southern Company Chair, Georgia Tech College of Engineering在 ece.gatech.edu 的电子邮件经过验证
