Daniel Arp
Daniel Arp
Dirección de correo verificada de
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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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Don’t paint it black: White-box explanations for deep learning in computer security
A Warnecke, D Arp, C Wressnegger, K Rieck
CoRR, 2019
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