Daniel Arp

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 22

Top Venues

CoRR

EuroS&P

AISec@CCS

USENIX Security Symposium

Braunschweig University of Technology, Germany (PHD)

Education History

Braunschweig University of Technology, Germany

PHD

Publications

Moritz Pfister, Robert Michael, Max Boll, Cosima Körfer, Konrad Rieck, Daniel Arp
Listening Between the Bits: Privacy Leaks in Audio Fingerprints. DIMVA (2024)
Zeliang Kan, Shae McFadden, Daniel Arp, Feargus Pendlebury, Roberto Jordaney, Johannes Kinder, Fabio Pierazzi, Lorenzo Cavallaro
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version). CoRR (2024)
Theo Chow, Zeliang Kan, Lorenz Linhardt, Lorenzo Cavallaro, Daniel Arp, Fabio Pierazzi
Drift Forensics of Malware Classifiers. AISec@CCS (2023)
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck
Lessons Learned on Machine Learning for Computer Security. IEEE Secur. Priv. 21 (5) (2023)
Vera Wesselkamp, Konrad Rieck, Daniel Arp, Erwin Quiring
Misleading Deep-Fake Detection with GAN Fingerprints. CoRR (2022)
Vera Wesselkamp, Konrad Rieck, Daniel Arp, Erwin Quiring
Misleading Deep-Fake Detection with GAN Fingerprints. SP Workshops (2022)
Stefan Czybik, Daniel Arp, Konrad Rieck
Quantifying the Risk of Wormhole Attacks on Bluetooth Contact Tracing. CODASPY (2022)
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck
Dos and Don'ts of Machine Learning in Computer Security. USENIX Security Symposium (2022)
Jan Malte Hilgefort, Daniel Arp, Konrad Rieck
Spying through Virtual Backgrounds of Video Calls. AISec@CCS (2021)
Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck
Evaluating Explanation Methods for Deep Learning in Security. EuroS&P (2020)
Erwin Quiring, Lukas Pirch, Michael Reimsbach, Daniel Arp, Konrad Rieck
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification. CoRR (2020)
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck
Dos and Don'ts of Machine Learning in Computer Security. CoRR (2020)
Erwin Quiring, David Klein, Daniel Arp, Martin Johns, Konrad Rieck
Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning. USENIX Security Symposium (2020)
Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck
Don't Paint It Black: White-Box Explanations for Deep Learning in Computer Security. CoRR (2019)
Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection. IEEE Trans. Dependable Secur. Comput. 16 (4) (2019)
Daniel Arp, Erwin Quiring, Tammo Krueger, Stanimir Dragiev, Konrad Rieck
Privacy-Enhanced Fraud Detection with Bloom Filters. SecureComm (1) (2018)
Erwin Quiring, Daniel Arp, Konrad Rieck
Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking. EuroS&P (2018)
Hugo Gascon, Bernd Grobauer, Thomas Schreck, Lukas Rist, Daniel Arp, Konrad Rieck
Mining Attributed Graphs for Threat Intelligence. CODASPY (2017)
Erwin Quiring, Daniel Arp, Konrad Rieck
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking. CoRR (2017)
Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection. CoRR (2017)
Daniel Arp, Erwin Quiring, Christian Wressnegger, Konrad Rieck
Privacy Threats through Ultrasonic Side Channels on Mobile Devices. EuroS&P (2017)
Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck
Comprehensive Analysis and Detection of Flash-Based Malware. DIMVA (2016)
Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck
Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols. SecureComm (2015)
Daniel Arp, Fabian Yamaguchi, Konrad Rieck
Torben: A Practical Side-Channel Attack for Deanonymizing Tor Communication. AsiaCCS (2015)
Michael Spreitzenbarth, Thomas Schreck, Florian Echtler, Daniel Arp, Johannes Hoffmann
Mobile-Sandbox: combining static and dynamic analysis with machine-learning techniques. Int. J. Inf. Sec. 14 (2) (2015)
Henning Perl, Sergej Dechand, Matthew Smith, Daniel Arp, Fabian Yamaguchi, Konrad Rieck, Sascha Fahl, Yasemin Acar
VCCFinder: Finding Potential Vulnerabilities in Open-Source Projects to Assist Code Audits. CCS (2015)
Fabian Yamaguchi, Nico Golde, Daniel Arp, Konrad Rieck
Modeling and Discovering Vulnerabilities with Code Property Graphs. IEEE Symposium on Security and Privacy (2014)
Daniel Arp, Michael Spreitzenbarth, Malte Hubner, Hugo Gascon, Konrad Rieck
DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket. NDSS (2014)
Christian Wressnegger, Guido Schwenk, Daniel Arp, Konrad Rieck
-grams in intrusion detection: anomaly detection vs. classification. AISec (2013)
Hugo Gascon, Fabian Yamaguchi, Daniel Arp, Konrad Rieck
Structural detection of android malware using embedded call graphs. AISec (2013)
Volker Eiselein, Daniel Arp, Michael Pätzold, Thomas Sikora
Real-Time Multi-human Tracking Using a Probability Hypothesis Density Filter and Multiple Detectors. AVSS (2012)

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Publication Activity (10 Years)

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Daniel Arp