ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models A Salem, Y Zhang, M Humbert, P Berrang, M Fritz, M Backes Annual Network and Distributed System Security Symposium (NDSS), 2019 | 903 | 2019 |
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples J Jinyuan, A Salem, M Backes, Y Zhang, NZ Gong ACM SIGSAC Conference on Computer and Communications Security (CCS), 259-274, 2019 | 381 | 2019 |
GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs D Chen, N Yu, Y Zhang, M Fritz ACM SIGSAC Conference on Computer and Communications Security (CCS), 343-362, 2020 | 358* | 2020 |
"Go eat a bat, Chang!": On the Emergence of Sinophobic Behavior on Web Communities in the Face of COVID-19 F Tahmasbi, L Schild, C Ling, J Blackburn, G Stringhini, Y Zhang, ... The Web Conference (WWW), 2021 | 349* | 2021 |
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements X Chen, A Salem, M Backes, S Ma, Y Zhang Annual Computer Security Applications Conference (ACSAC), 2021 | 317 | 2021 |
Dynamic Backdoor Attacks Against Machine Learning Models A Salem, R Wen, M Backes, S Ma, Y Zhang IEEE European Symposium on Security and Privacy (EuroS&P), 2020 | 273 | 2020 |
Membership Leakage in Label-Only Exposures Z Li, Y Zhang ACM SIGSAC Conference on Computer and Communications Security (CCS), 2021 | 261* | 2021 |
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning A Salem, A Bhattacharya, M Backes, M Fritz, Y Zhang USENIX Security Symposium (USENIX Security), 1291-1308, 2020 | 255 | 2020 |
When Machine Unlearning Jeopardizes Privacy M Chen, Z Zhang, T Wang, M Backes, M Humbert, Y Zhang ACM SIGSAC Conference on Computer and Communications Security (CCS), 2021 | 199 | 2021 |
"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models X Shen, Z Chen, M Backes, Y Shen, Y Zhang arXiv preprint arXiv:2308.03825, 2023 | 193 | 2023 |
Fairwalk: Towards Fair Graph Embedding T Rahman, B Surma, M Backes, Y Zhang International Joint Conference on Artificial Intelligence (IJCAI), 3289-3295, 2019 | 189 | 2019 |
How to Prove Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN Z Li, C Hu, Y Zhang, S Guo Annual Computer Security Applications Conference (ACSAC), 126-137, 2019 | 174 | 2019 |
Stealing Links from Graph Neural Networks X He, J Jia, M Backes, NZ Gong, Y Zhang USENIX Security Symposium (USENIX Security), 2021 | 148 | 2021 |
walk2friends: Inferring Social Links from Mobility Profiles M Backes, M Humbert, J Pang, Y Zhang ACM SIGSAC Conference on Computer and Communications Security (CCS), 1943-1957, 2017 | 137 | 2017 |
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service L Hanzlik, Y Zhang, K Grosse, A Salem, M Augustin, M Backes, M Fritz arXiv preprint arXiv:1808.00590, 2018 | 115 | 2018 |
Graph Unlearning M Chen, Z Zhang, T Wang, M Backes, M Humbert, Y Zhang ACM SIGSAC Conference on Computer and Communications Security (CCS), 2022 | 110 | 2022 |
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Y Liu, R Wen, X He, A Salem, Z Zhang, M Backes, E De Cristofaro, M Fritz, ... USENIX Security Symposium (USENIX Security), 2022 | 110 | 2022 |
Inference Attacks Against Graph Neural Networks Z Zhang, M Chen, M Backes, Y Shen, Y Zhang USENIX Security Symposium (USENIX Security), 2022 | 99 | 2022 |
Privsyn: Differentially Private Data Synthesis Z Zhang, T Wang, N Li, J Honorio, M Backes, S He, J Chen, Y Zhang USENIX Security Symposium (USENIX Security), 2021 | 96 | 2021 |
A New Access Control Scheme for Facebook-style Social Networks J Pang, Y Zhang Computers & Security 54, 44-59, 2015 | 92 | 2015 |