| 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 | 976 | 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 | 412 | 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 | 400* | 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 | 367* | 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 | 359 | 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 | 311 | 2020 |
| Membership Leakage in Label-Only Exposures Z Li, Y Zhang ACM SIGSAC Conference on Computer and Communications Security (CCS), 2021 | 290* | 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 | 276 | 2020 |
| "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 | 262 | 2023 |
| 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 | 220 | 2021 |
| Fairwalk: Towards Fair Graph Embedding T Rahman, B Surma, M Backes, Y Zhang International Joint Conference on Artificial Intelligence (IJCAI), 3289-3295, 2019 | 203 | 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 | 190 | 2019 |
| Stealing Links from Graph Neural Networks X He, J Jia, M Backes, NZ Gong, Y Zhang USENIX Security Symposium (USENIX Security), 2021 | 163 | 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 | 142 | 2017 |
| Graph Unlearning M Chen, Z Zhang, T Wang, M Backes, M Humbert, Y Zhang ACM SIGSAC Conference on Computer and Communications Security (CCS), 2022 | 134 | 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 | 130 | 2022 |
| 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 | 124 | 2018 |
| DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Diffusion Models Z Sha, Z Li, N Yu, Y Zhang ACM SIGSAC Conference on Computer and Communications Security (CCS), 2023 | 122* | 2023 |
| Inference Attacks Against Graph Neural Networks Z Zhang, M Chen, M Backes, Y Shen, Y Zhang USENIX Security Symposium (USENIX Security), 2022 | 116 | 2022 |
| In ChatGPT We Trust? Measuring and Characterizing the Reliability of ChatGPT X Shen, Z Chen, M Backes, Y Zhang arXiv preprint arXiv:2304.08979, 2023 | 108 | 2023 |
Michael BackesChairman and Founding Director of the CISPA Helmholtz Center for Information SecurityVerified email at cispa.saarland
