Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning

Computer Viruses: Theory and Experiments

F. Cohen · 1987

Earlier work this paper cites.

Fast effective rule induction

W. W. Cohen · 1995

Earlier work this paper cites.

Reinforcement learning: An introduction

R. S. Sutton and A. G. Barto · 1998

Earlier work this paper cites.

Actor-critic algorithms

V. R. Konda and J. N. Tsitsiklis · 2000

Earlier work this paper cites.

Data mining methods for detection of new malicious executables

M. G. Schultz, E. Eskin, F. Zadok, and S. J. Stolfo · 2001

Earlier work this paper cites.

Learning to detect malicious executables in the wild

J. Z. Kolter and M. A. Maloof · 2004

Earlier work this paper cites.

A framework for efficient mining of structural information to detect zero-day malicious portable executables

M. Z. Shafiq, S. M. Tabish, F. Mirza, and M. Farooq · 2009

Earlier work this paper cites.

Selecting features to classify malware

K. Raman et al · 2012

Earlier work this paper cites.

Large-scale malware classification using random projections and neural networks

G. E. Dahl, J. W. Stokes, L. Deng, and D. Yu · 2013

Earlier work this paper cites.

Playing atari with deep reinforcement learning

Original

V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller · 2013

Earlier work this paper cites.

Intriguing properties of neural networks

Original

C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2013

Earlier work this paper cites.

Generative adversarial nets

I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014

Cited alongside, same era.

Explaining and harnessing adversarial examples

Original

I. J. Goodfellow, J. Shlens, and C. Szegedy · 2014

Cited alongside, same era.

Deep reinforcement learning in large discrete action spaces

Original

G. Dulac-Arnold, R. Evans, H. van Hasselt, P. Sunehag, T. Lillicrap, J. Hunt, T. Mann, T. Weber, T. Degris, and B. Coppin · 2015

Cited alongside, same era.

Human-level control through deep reinforcement learning

V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, et al · 2015

Cited alongside, same era.

Distillation as a defense to adversarial perturbations against deep neural networks

N. Papernot, P. McDaniel, X. Wu, S. Jha, and A. Swami · 2015

Cited alongside, same era.

Adversarial perturbations against deep neural networks for malware classification

Original

K. Grosse, N. Papernot, P. Manoharan, M. Backes, and P. McDaniel · 2016

Later among the works it cites.

Sample efficient actor-critic with experience replay

Original

Z. Wang, V. Bapst, N. Heess, V. Mnih, R. Munos, K. Kavukcuoglu, and N. de Freitas · 2016

Later among the works it cites.

Automatically evading classifiers

W. Xu, Y. Qi, and D. Evans · 2016

Later among the works it cites.

Evading machine learning malware detection

H. S. Anderson, A. Kharkar, B. Filar, and P. Roth · 2017

Later among the works it cites.

Malware classification with LSTM and GRU language models and a character-level CNN

B. Athiwaratkun and J. W. Stokes · 2017

Later among the works it cites.