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Robust and Effective Malware Detection through Quantitative Data Flow
  Graph Metrics
v1v2 (latest)

Robust and Effective Malware Detection through Quantitative Data Flow Graph Metrics

5 February 2015
Tobias Wüchner
Martín Ochoa
A. Pretschner
ArXiv (abs)PDFHTML

Papers citing "Robust and Effective Malware Detection through Quantitative Data Flow Graph Metrics"

5 / 5 papers shown
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box
  Android Malware Detection
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection
Hamid Bostani
Veelasha Moonsamy
AAML
532
78
0
07 Oct 2021
Mal2GCN: A Robust Malware Detection Approach Using Deep Graph
  Convolutional Networks With Non-Negative Weights
Mal2GCN: A Robust Malware Detection Approach Using Deep Graph Convolutional Networks With Non-Negative WeightsJournal of Computer Virology and Hacking Techniques (JCVHT), 2021
Omid Kargarnovin
A. M. Sadeghzadeh
R. Jalili
AAML
327
15
0
27 Aug 2021
Tools and Techniques for Malware Detection and Analysis
Sajedul Talukder
149
36
0
17 Feb 2020
Bin2vec: Learning Representations of Binary Executable Programs for
  Security Tasks
Bin2vec: Learning Representations of Binary Executable Programs for Security Tasks
Shushan Arakelyan
Sima Arasteh
Christophe Hauser
Erik Kline
Aram Galstyan
336
26
0
09 Feb 2020
Survey of Machine Learning Techniques for Malware Analysis
Survey of Machine Learning Techniques for Malware AnalysisComputers & security (Comput. Secur.), 2017
Daniele Ucci
Leonardo Aniello
R. Baldoni
446
345
0
23 Oct 2017
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