| Drebin: Effective and explainable detection of android malware in your pocket. D Arp, M Spreitzenbarth, M Hubner, H Gascon, K Rieck 21st Annual Network and Distributed System Security Symposium (NDSS) 14, 23-26, 2014 | 2757 | 2014 |
| Modeling and discovering vulnerabilities with code property graphs F Yamaguchi, N Golde, D Arp, K Rieck 2014 IEEE symposium on security and privacy, 590-604, 2014 | 810 | 2014 |
| Structural detection of android malware using embedded call graphs H Gascon, F Yamaguchi, D Arp, K Rieck Proceedings of the 2013 ACM workshop on Artificial intelligence and security …, 2013 | 420 | 2013 |
| Yes, machine learning can be more secure! a case study on android malware detection A Demontis, M Melis, B Biggio, D Maiorca, D Arp, K Rieck, I Corona, ... IEEE transactions on dependable and secure computing 16 (4), 711-724, 2017 | 344 | 2017 |
| Dos and don'ts of machine learning in computer security D Arp, E Quiring, F Pendlebury, A Warnecke, F Pierazzi, C Wressnegger, ... Proceedings of the 31th USENIX Conference on Security Symposium, 3971-3988, 2022 | 320 | 2022 |
| Vccfinder: Finding potential vulnerabilities in open-source projects to assist code audits H Perl, S Dechand, M Smith, D Arp, F Yamaguchi, K Rieck, S Fahl, Y Acar Proceedings of the 22nd ACM SIGSAC conference on computer and communications …, 2015 | 284 | 2015 |
| 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 | 157 | 2015 |
| Mobile-Sandbox: combining static and dynamic analysis with machine-learning techniques M Spreitzenbarth, T Schreck, F Echtler, D Arp, J Hoffmann International Journal of Information Security 14, 141-153, 2015 | 140 | 2015 |
| 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 | 134 | 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 | 107 | 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 | 95 | 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 | 83 | 2018 |
| 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), 1363-1380, 2020 | 79 | 2020 |
| Real-time multi-human tracking using a probability hypothesis density filter and multiple detectors V Eiselein, D Arp, M Pätzold, T Sikora 2012 IEEE Ninth international conference on advanced video and signal-based …, 2012 | 76 | 2012 |
| Torben: A practical side-channel attack for deanonymizing tor communication D Arp, F Yamaguchi, K Rieck Proceedings of the 10th ACM Symposium on Information, Computer and …, 2015 | 40 | 2015 |
| Mining attributed graphs for threat intelligence H Gascon, B Grobauer, T Schreck, L Rist, D Arp, K Rieck Proceedings of the Seventh ACM on Conference on Data and Application …, 2017 | 39 | 2017 |
| 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 | 32 | 2016 |
| 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 | 12 | 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 |
| Don’t paint it black: White-box explanations for deep learning in computer security A Warnecke, D Arp, C Wressnegger, K Rieck CoRR, 2019 | 10 | 2019 |
Konrad RieckTechnische Universität Berlin在 tu-berlin.de 的电子邮件经过验证
