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Stealing and Evading Malware Classifiers and Antivirus at Low False
  Positive Conditions

Stealing and Evading Malware Classifiers and Antivirus at Low False Positive Conditions

13 April 2022
M. Rigaki
Sebastian Garcia
    AAML
ArXivPDFHTML

Papers citing "Stealing and Evading Malware Classifiers and Antivirus at Low False Positive Conditions"

5 / 5 papers shown
Title
The Power of MEME: Adversarial Malware Creation with Model-Based
  Reinforcement Learning
The Power of MEME: Adversarial Malware Creation with Model-Based Reinforcement Learning
M. Rigaki
Sebastian Garcia
AAML
20
4
0
31 Aug 2023
Bypassing antivirus detection: old-school malware, new tricks
Bypassing antivirus detection: old-school malware, new tricks
Efstratios Chatzoglou
Georgios Karopoulos
G. Kambourakis
Zisis Tsiatsikas
12
7
0
06 May 2023
secml-malware: Pentesting Windows Malware Classifiers with Adversarial
  EXEmples in Python
secml-malware: Pentesting Windows Malware Classifiers with Adversarial EXEmples in Python
Luca Demetrio
Battista Biggio
AAML
35
11
0
26 Apr 2021
Cryptanalytic Extraction of Neural Network Models
Cryptanalytic Extraction of Neural Network Models
Nicholas Carlini
Matthew Jagielski
Ilya Mironov
FedML
MLAU
MIACV
AAML
70
134
0
10 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
1