| {T-Miner}: A generative approach to defend against trojan attacks on {DNN-based} text classification A Azizi, IA Tahmid, A Waheed, N Mangaokar, J Pu, M Javed, CK Reddy, ... 30th USENIX Security Symposium (USENIX Security 21), 2255-2272, 2021 | 110 | 2021 |
| Throwing darts in the dark? detecting bots with limited data using neural data augmentation STK Jan, Q Hao, T Hu, J Pu, S Oswal, G Wang, B Viswanath 2020 IEEE symposium on security and privacy (SP), 1190-1206, 2020 | 86 | 2020 |
| Deepfake text detection: Limitations and opportunities J Pu, Z Sarwar, SM Abdullah, A Rehman, Y Kim, P Bhattacharya, M Javed, ... 2023 IEEE symposium on security and privacy (SP), 1613-1630, 2023 | 67 | 2023 |
| Deepfake videos in the wild: Analysis and detection J Pu, N Mangaokar, L Kelly, P Bhattacharya, K Sundaram, M Javed, ... Proceedings of the Web Conference 2021, 981-992, 2021 | 58 | 2021 |
| Jekyll: Attacking medical image diagnostics using deep generative models N Mangaokar, J Pu, P Bhattacharya, CK Reddy, B Viswanath 2020 IEEE European Symposium on Security and Privacy (EuroS&P), 139-157, 2020 | 44 | 2020 |
| Noisescope: Detecting deepfake images in a blind setting J Pu, N Mangaokar, B Wang, CK Reddy, B Viswanath Proceedings of the 36th Annual Computer Security Applications Conference …, 2020 | 34 | 2020 |
| Multiview clustering based on robust and regularized matrix approximation J Pu, Q Zhang, L Zhang, B Du, J You 2016 23rd International Conference on Pattern Recognition (ICPR), 2550-2555, 2016 | 14 | 2016 |
| Defending Against Misuse of Synthetic Media: Characterizing Real-world Challenges and Building Robust Defenses J Pu Virginia Tech, 2022 | | 2022 |
| Tan, Te Juin Lester 175 Tang, Haixu 521 Towa, Patrick 405 Treharne, Helen 425 J Koschel, E Koutsoupias, B Kreuter, R Küsters, X Lan, A Lehmann, ... | | |
