Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDDaniel Arp
Person information
- affiliation (PhD 2019): Braunschweig University of Technology, Germany
- affiliation: University of Göttingen, Germany
- affiliation: TU Berlin, Germany
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[i7]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 abs/2402.01359 (2024)- 2023
- [j3]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): 72-77 (2023) - [c20]Theo Chow, Zeliang Kan, Lorenz Linhardt, Lorenzo Cavallaro, Daniel Arp, Fabio Pierazzi:
Drift Forensics of Malware Classifiers. AISec@CCS 2023: 197-207 - 2022
- [c19]Stefan Czybik, Daniel Arp, Konrad Rieck:
Quantifying the Risk of Wormhole Attacks on Bluetooth Contact Tracing. CODASPY 2022: 264-275 - [c18]Vera Wesselkamp, Konrad Rieck, Daniel Arp, Erwin Quiring:
Misleading Deep-Fake Detection with GAN Fingerprints. SP (Workshops) 2022: 59-65 - [c17]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: 3971-3988 - [e1]Christian Wressnegger, Delphine Reinhardt, Thomas Barber, Bernhard C. Witt, Daniel Arp, Zoltán Ádám Mann:
Sicherheit, Schutz und Zuverlässigkeit: Konferenzband der 11. Jahrestagung des Fachbereichs Sicherheit der Gesellschaft für Informatik e.V. (GI), Sicherheit 2022, Karlsruhe, Germany, April 5-8, 2022. LNI P-323, Gesellschaft für Informatik, Bonn 2022, ISBN 978-3-88579-717-3 [contents] - [i6]Vera Wesselkamp, Konrad Rieck, Daniel Arp, Erwin Quiring:
Misleading Deep-Fake Detection with GAN Fingerprints. CoRR abs/2205.12543 (2022) - 2021
- [c16]Jan Malte Hilgefort, Daniel Arp, Konrad Rieck:
Spying through Virtual Backgrounds of Video Calls. AISec@CCS 2021: 135-144 - 2020
- [c15]Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck:
Evaluating Explanation Methods for Deep Learning in Security. EuroS&P 2020: 158-174 - [c14]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: 1363-1380 - [i5]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 abs/2010.09470 (2020) - [i4]Erwin Quiring, Lukas Pirch, Michael Reimsbach, Daniel Arp, Konrad Rieck:
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification. CoRR abs/2010.09569 (2020)
2010 – 2019
- 2019
- [b1]Daniel Arp:
Efficient and Explainable Detection of Mobile Malware with Machine Learning. Braunschweig University of Technology, Germany, 2019 - [j2]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): 711-724 (2019) - [p1]Daniel Arp:
Erkennung mobiler Schadsoftware mit maschinellen Lernverfahren. Ausgezeichnete Informatikdissertationen 2019: 9-18 - [i3]Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck:
Don't Paint It Black: White-Box Explanations for Deep Learning in Computer Security. CoRR abs/1906.02108 (2019) - 2018
- [c13]Erwin Quiring, Daniel Arp, Konrad Rieck:
Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking. EuroS&P 2018: 488-502 - [c12]Daniel Arp, Erwin Quiring, Tammo Krueger, Stanimir Dragiev, Konrad Rieck:
Privacy-Enhanced Fraud Detection with Bloom Filters. SecureComm (1) 2018: 396-415 - 2017
- [c11]Hugo Gascon, Bernd Grobauer, Thomas Schreck, Lukas Rist, Daniel Arp, Konrad Rieck:
Mining Attributed Graphs for Threat Intelligence. CODASPY 2017: 15-22 - [c10]Daniel Arp, Erwin Quiring, Christian Wressnegger, Konrad Rieck:
Privacy Threats through Ultrasonic Side Channels on Mobile Devices. EuroS&P 2017: 35-47 - [i2]Erwin Quiring, Daniel Arp, Konrad Rieck:
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking. CoRR abs/1703.05561 (2017) - [i1]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 abs/1704.08996 (2017) - 2016
- [c9]Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck:
Comprehensive Analysis and Detection of Flash-Based Malware. DIMVA 2016: 101-121 - 2015
- [j1]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): 141-153 (2015) - [c8]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: 426-437 - [c7]Daniel Arp, Fabian Yamaguchi, Konrad Rieck:
Torben: A Practical Side-Channel Attack for Deanonymizing Tor Communication. AsiaCCS 2015: 597-602 - [c6]Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck:
Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols. SecureComm 2015: 330-347 - 2014
- [c5]Daniel Arp, Michael Spreitzenbarth, Malte Hubner, Hugo Gascon, Konrad Rieck:
DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket. NDSS 2014 - [c4]Fabian Yamaguchi, Nico Golde, Daniel Arp, Konrad Rieck:
Modeling and Discovering Vulnerabilities with Code Property Graphs. IEEE Symposium on Security and Privacy 2014: 590-604 - 2013
- [c3]Hugo Gascon, Fabian Yamaguchi, Daniel Arp, Konrad Rieck:
Structural detection of android malware using embedded call graphs. AISec 2013: 45-54 - [c2]Christian Wressnegger, Guido Schwenk, Daniel Arp, Konrad Rieck:
A close look on n-grams in intrusion detection: anomaly detection vs. classification. AISec 2013: 67-76 - 2012
- [c1]Volker Eiselein, Daniel Arp, Michael Pätzold, Thomas Sikora:
Real-Time Multi-human Tracking Using a Probability Hypothesis Density Filter and Multiple Detectors. AVSS 2012: 325-330
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-04-25 05:59 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
