| Dos and don'ts of machine learning in computer security D Arp, E Quiring, F Pendlebury, A Warnecke, F Pierazzi, C Wressnegger, ... 31st USENIX Security Symposium (USENIX Security 22), 3971-3988, 2022 | 328 | 2022 |
| Misleading authorship attribution of source code using adversarial learning E Quiring, A Maier, K Rieck 28th {USENIX} Security Symposium ({USENIX} Security 19), 479-496, 2019 | 116 | 2019 |
| Privacy threats through ultrasonic side channels on mobile devices D Arp, E Quiring, C Wressnegger, K Rieck 2017 IEEE European Symposium on Security and Privacy (EuroS&P), 35-47, 2017 | 96 | 2017 |
| Forgotten siblings: Unifying attacks on machine learning and digital watermarking E Quiring, D Arp, K Rieck 2018 IEEE European Symposium on Security and Privacy (EuroS&P), 488-502, 2018 | 92 | 2018 |
| Backdooring and poisoning neural networks with image-scaling attacks E Quiring, K Rieck 2020 IEEE Security and Privacy Workshops (SPW), 41-47, 2020 | 80 | 2020 |
| Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning E Quiring, D Klein, D Arp, M Johns, K Rieck 29th {USENIX} Security Symposium ({USENIX} Security 20), 2020 | 80 | 2020 |
| Fragile sensor fingerprint camera identification E Quiring, M Kirchner 2015 IEEE International Workshop on Information Forensics and Security (WIFS …, 2015 | 29 | 2015 |
| Adversarial Machine Learning Against Digital Watermarking E Quiring, K Rieck 2018 26th European Signal Processing Conference (EUSIPCO), 519-523, 2018 | 18 | 2018 |
| Misleading Deep-Fake Detection with GAN Fingerprints V Wesselkamp, K Rieck, D Arp, E Quiring 2022 IEEE Security and Privacy Workshops (SPW), 59-65, 2022 | 13 | 2022 |
| Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification E Quiring, L Pirch, M Reimsbach, D Arp, K Rieck arXiv preprint arXiv:2010.09569, 2020 | 11 | 2020 |
| On the security and applicability of fragile camera fingerprints E Quiring, M Kirchner, K Rieck Computer Security–ESORICS 2019: 24th European Symposium on Research in …, 2019 | 7 | 2019 |
| Privacy-Enhanced Fraud Detection with Bloom Filters D Arp, E Quiring, T Krueger, S Dragiev, K Rieck International Conference on Security and Privacy in Communication Systems …, 2018 | 7 | 2018 |
| Bat in the Mobile: A Study on Ultrasonic Device Tracking D Arp, E Quiring, C Wressnegger, K Rieck Computer Science Report 2016-02, 2016 | 7 | 2016 |
| No more Reviewer# 2: Subverting Automatic {Paper-Reviewer} Assignment using Adversarial Learning T Eisenhofer, E Quiring, J Möller, D Riepel, T Holz, K Rieck 32nd USENIX Security Symposium (USENIX Security 23), 5109-5126, 2023 | 5 | 2023 |
| On the Detection of Image-Scaling Attacks in Machine Learning E Quiring, A Müller, K Rieck Proceedings of the 39th Annual Computer Security Applications Conference …, 2023 | 1 | 2023 |
| Lessons Learned on Machine Learning for Computer Security D Arp, E Quiring, F Pendlebury, A Warnecke, F Pierazzi, C Wressnegger, ... IEEE Security & Privacy 21 (5), 72-77, 2023 | 1 | 2023 |
| I still know it's you! On Challenges in Anonymizing Source Code M Horlboge, E Quiring, R Meyer, K Rieck arXiv preprint arXiv:2208.12553, 2022 | 1 | 2022 |
| AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images J Ricker, D Assenmacher, T Holz, A Fischer, E Quiring arXiv preprint arXiv:2404.14244, 2024 | | 2024 |
| The Impact of Uniform Inputs on Activation Sparsity and Energy-Latency Attacks in Computer Vision A Müller, E Quiring arXiv preprint arXiv:2403.18587, 2024 | | 2024 |
| On the Security of Machine Learning Beyond the Feature Space E Quiring | | 2021 |
Konrad RieckTechnische Universität Berlin在 tu-berlin.de 的电子邮件经过验证
