Daniel Arp

According to our database, Daniel Arp authored at least 29 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version).

Zeliang Kan, Shae McFadden, Daniel Arp, Feargus Pendlebury, Roberto Jordaney, Johannes Kinder, Fabio Pierazzi, Lorenzo Cavallaro

CoRR, 2024

2023

Lessons Learned on Machine Learning for Computer Security.

Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck

IEEE Secur. Priv., 2023

Drift Forensics of Malware Classifiers.

Theo Chow, Zeliang Kan, Lorenz Linhardt, Lorenzo Cavallaro, Daniel Arp, Fabio Pierazzi

Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023

2022

Dos and Don'ts of Machine Learning in Computer Security.

Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck

Proceedings of the 31st USENIX Security Symposium, 2022

Misleading Deep-Fake Detection with GAN Fingerprints.

Vera Wesselkamp, Konrad Rieck, Daniel Arp, Erwin Quiring

Proceedings of the 43rd IEEE Security and Privacy, 2022

Quantifying the Risk of Wormhole Attacks on Bluetooth Contact Tracing.

Stefan Czybik, Daniel Arp, Konrad Rieck

Proceedings of the CODASPY '22: Twelveth ACM Conference on Data and Application Security and Privacy, Baltimore, MD, USA, April 24, 2022

2021

Spying through Virtual Backgrounds of Video Calls.

Jan Malte Hilgefort, Daniel Arp, Konrad Rieck

Proceedings of the AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021

2020

Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification.

Erwin Quiring, Lukas Pirch, Michael Reimsbach, Daniel Arp, Konrad Rieck

CoRR, 2020

Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning.

Erwin Quiring, David Klein, Daniel Arp, Martin Johns, Konrad Rieck

Proceedings of the 29th USENIX Security Symposium, 2020

Evaluating Explanation Methods for Deep Learning in Security.

Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck

Proceedings of the IEEE European Symposium on Security and Privacy, 2020

2019

Erkennung mobiler Schadsoftware mit maschinellen Lernverfahren.

Daniel Arp

Proceedings of the Ausgezeichnete Informatikdissertationen 2019., 2019

Efficient and Explainable Detection of Mobile Malware with Machine Learning.

Daniel Arp

PhD thesis, 2019

Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection.

Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli

IEEE Trans. Dependable Secur. Comput., 2019

Don't Paint It Black: White-Box Explanations for Deep Learning in Computer Security.

Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck

CoRR, 2019

2018

Privacy-Enhanced Fraud Detection with Bloom Filters.

Daniel Arp, Erwin Quiring, Tammo Krueger, Stanimir Dragiev, Konrad Rieck

Proceedings of the Security and Privacy in Communication Networks, 2018

Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking.

Erwin Quiring, Daniel Arp, Konrad Rieck

Proceedings of the 2018 IEEE European Symposium on Security and Privacy, 2018

2017

Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking.

Erwin Quiring, Daniel Arp, Konrad Rieck

CoRR, 2017

Privacy Threats through Ultrasonic Side Channels on Mobile Devices.

Daniel Arp, Erwin Quiring, Christian Wressnegger, Konrad Rieck

Proceedings of the 2017 IEEE European Symposium on Security and Privacy, 2017

Mining Attributed Graphs for Threat Intelligence.

Hugo Gascon, Bernd Grobauer, Thomas Schreck, Lukas Rist, Daniel Arp, Konrad Rieck

Proceedings of the Seventh ACM Conference on Data and Application Security and Privacy, 2017

2016

Comprehensive Analysis and Detection of Flash-Based Malware.

Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck

Proceedings of the Detection of Intrusions and Malware, and Vulnerability Assessment, 2016

2015

Mobile-Sandbox: combining static and dynamic analysis with machine-learning techniques.

Michael Spreitzenbarth, Thomas Schreck, Florian Echtler, Daniel Arp, Johannes Hoffmann

Int. J. Inf. Sec., 2015

Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols.

Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck

Proceedings of the Security and Privacy in Communication Networks, 2015

VCCFinder: Finding Potential Vulnerabilities in Open-Source Projects to Assist Code Audits.

Henning Perl, Sergej Dechand, Matthew Smith, Daniel Arp, Fabian Yamaguchi, Konrad Rieck, Sascha Fahl, Yasemin Acar

Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015

Torben: A Practical Side-Channel Attack for Deanonymizing Tor Communication.

Daniel Arp, Fabian Yamaguchi, Konrad Rieck

Proceedings of the 10th ACM Symposium on Information, 2015

2014

Modeling and Discovering Vulnerabilities with Code Property Graphs.

Fabian Yamaguchi, Nico Golde, Daniel Arp, Konrad Rieck

Proceedings of the 2014 IEEE Symposium on Security and Privacy, 2014

DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket.

Daniel Arp, Michael Spreitzenbarth, Malte Hubner, Hugo Gascon, Konrad Rieck

Proceedings of the 21st Annual Network and Distributed System Security Symposium, 2014

2013

A close look on <i>n</i>-grams in intrusion detection: anomaly detection vs. classification.

Christian Wressnegger, Guido Schwenk, Daniel Arp, Konrad Rieck

Proceedings of the AISec'13, 2013

Structural detection of android malware using embedded call graphs.

Hugo Gascon, Fabian Yamaguchi, Daniel Arp, Konrad Rieck

Proceedings of the AISec'13, 2013

2012

Real-Time Multi-human Tracking Using a Probability Hypothesis Density Filter and Multiple Detectors.

Volker Eiselein, Daniel Arp, Michael Pätzold, Thomas Sikora

Proceedings of the Ninth IEEE International Conference on Advanced Video and Signal-Based Surveillance, 2012