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A Survey of Machine Learning Methods and Challenges for Windows Malware
  Classification

A Survey of Machine Learning Methods and Challenges for Windows Malware Classification

15 June 2020
Edward Raff
Charles K. Nicholas
    AAML
ArXivPDFHTML

Papers citing "A Survey of Machine Learning Methods and Challenges for Windows Malware Classification"

8 / 8 papers shown
Title
MalMixer: Few-Shot Malware Classification with Retrieval-Augmented Semi-Supervised Learning
MalMixer: Few-Shot Malware Classification with Retrieval-Augmented Semi-Supervised Learning
Eric Li
Yifan Zhang
Yu Huang
Kevin Leach
26
0
0
20 Sep 2024
Layered Uploading for Quantum Convolutional Neural Networks
Layered Uploading for Quantum Convolutional Neural Networks
Grégoire Barrué
Tony Quertier
Orlane Zang
89
0
0
15 Apr 2024
Marvolo: Programmatic Data Augmentation for Practical ML-Driven Malware
  Detection
Marvolo: Programmatic Data Augmentation for Practical ML-Driven Malware Detection
Michael D. Wong
Edward Raff
James Holt
Ravi Netravali
21
2
0
07 Jun 2022
Rank-1 Similarity Matrix Decomposition For Modeling Changes in Antivirus
  Consensus Through Time
Rank-1 Similarity Matrix Decomposition For Modeling Changes in Antivirus Consensus Through Time
R. Joyce
Edward Raff
Charles K. Nicholas
22
5
0
28 Dec 2021
Adversarial Attacks against Windows PE Malware Detection: A Survey of
  the State-of-the-Art
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art
Xiang Ling
Lingfei Wu
Jiangyu Zhang
Zhenqing Qu
Wei Deng
...
Chunming Wu
S. Ji
Tianyue Luo
Jingzheng Wu
Yanjun Wu
AAML
28
72
0
23 Dec 2021
MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels
MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels
R. Joyce
Dev Amlani
B. Hamilton
Edward Raff
24
21
0
29 Nov 2021
A Framework for Cluster and Classifier Evaluation in the Absence of
  Reference Labels
A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels
R. Joyce
Edward Raff
Charles K. Nicholas
41
16
0
23 Sep 2021
ranger: A Fast Implementation of Random Forests for High Dimensional
  Data in C++ and R
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
Marvin N. Wright
A. Ziegler
93
2,731
0
18 Aug 2015
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