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 | 406 | 2022 |
Chucky: Exposing missing checks in source code for vulnerability discovery F Yamaguchi, C Wressnegger, H Gascon, K Rieck Proceedings of the 2013 ACM SIGSAC conference on Computer & communications …, 2013 | 240 | 2013 |
Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols H Gascon, C Wressnegger, F Yamaguchi, D Arp, K Rieck Security and Privacy in Communication Networks: 11th EAI International …, 2015 | 180 | 2015 |
Poisoning behavioral malware clustering B Biggio, K Rieck, D Ariu, C Wressnegger, I Corona, G Giacinto, F Roli Proceedings of the 2014 workshop on artificial intelligent and security …, 2014 | 172 | 2014 |
Machine unlearning of features and labels A Warnecke, L Pirch, C Wressnegger, K Rieck arXiv preprint arXiv:2108.11577, 2021 | 155 | 2021 |
A close look on n-grams in intrusion detection: anomaly detection vs. classification C Wressnegger, G Schwenk, D Arp, K Rieck Proceedings of the 2013 ACM workshop on Artificial intelligence and security …, 2013 | 138 | 2013 |
Evaluating explanation methods for deep learning in security A Warnecke, D Arp, C Wressnegger, K Rieck 2020 IEEE european symposium on security and privacy (EuroS&P), 158-174, 2020 | 133 | 2020 |
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 | 105 | 2017 |
New Kid on the Web: A Study on the Prevalence of WebAssembly in the Wild M Musch, C Wressnegger, M Johns, K Rieck Detection of Intrusions and Malware, and Vulnerability Assessment: 16th …, 2019 | 82 | 2019 |
Automatically inferring malware signatures for anti-virus assisted attacks C Wressnegger, K Freeman, F Yamaguchi, K Rieck Proceedings of the 2017 ACM on Asia conference on computer and …, 2017 | 62 | 2017 |
Thieves in the browser: Web-based cryptojacking in the wild M Musch, C Wressnegger, M Johns, K Rieck Proceedings of the 14th International Conference on Availability …, 2019 | 58 | 2019 |
Zoe: Content-based anomaly detection for industrial control systems C Wressnegger, A Kellner, K Rieck 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems …, 2018 | 44 | 2018 |
Web-based Cryptojacking in the Wild M Musch, C Wressnegger, M Johns, K Rieck arXiv preprint arXiv:1808.09474, 2018 | 42 | 2018 |
TypeMiner: Recovering types in binary programs using machine learning A Maier, H Gascon, C Wressnegger, K Rieck Detection of Intrusions and Malware, and Vulnerability Assessment: 16th …, 2019 | 39 | 2019 |
Reproducibility and replicability of web measurement studies N Demir, M Große-Kampmann, T Urban, C Wressnegger, T Holz, ... Proceedings of the ACM Web Conference 2022, 533-544, 2022 | 38 | 2022 |
Comprehensive analysis and detection of flash-based malware C Wressnegger, F Yamaguchi, D Arp, K Rieck Detection of Intrusions and Malware, and Vulnerability Assessment: 13th …, 2016 | 38* | 2016 |
False sense of security: A study on the effectivity of jailbreak detection in banking apps A Kellner, M Horlboge, K Rieck, C Wressnegger 2019 IEEE European Symposium on Security and Privacy (EuroS&P), 1-14, 2019 | 29 | 2019 |
Sally: A tool for embedding strings in vector spaces K Rieck, C Wressnegger, A Bikadorov The Journal of Machine Learning Research 13 (1), 3247-3251, 2012 | 27 | 2012 |
Harry: A tool for measuring string similarity K Rieck, C Wressnegger The Journal of Machine Learning Research 17 (1), 258-262, 2016 | 25 | 2016 |
Disguising attacks with explanation-aware backdoors M Noppel, L Peter, C Wressnegger 2023 IEEE Symposium on Security and Privacy (SP), 664-681, 2023 | 21* | 2023 |