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

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

26 January 2018
Hyrum S. Anderson
Anant Kharkar
Bobby Filar
David E. Evans
P. Roth
    AAML
ArXivPDFHTML

Papers citing "Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning"

22 / 22 papers shown
Title
Reinforcement Learning for an Efficient and Effective Malware Investigation during Cyber Incident Response
Reinforcement Learning for an Efficient and Effective Malware Investigation during Cyber Incident Response
Dipo Dunsin
M. C. Ghanem
Karim Ouazzane
Vassil T. Vassilev
44
5
0
08 Jan 2025
EGAN: Evolutional GAN for Ransomware Evasion
EGAN: Evolutional GAN for Ransomware Evasion
Daniel Commey
Benjamin Appiah
B. K. Frimpong
Isaac Osei
Ebenezer N. A. Hammond
Garth V. Crosby
AAML
GAN
29
0
0
20 May 2024
Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples
Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples
M. Kozák
Luca Demetrio
Dmitrijs Trizna
Fabio Roli
AAML
36
0
0
04 May 2024
The Adaptive Arms Race: Redefining Robustness in AI Security
The Adaptive Arms Race: Redefining Robustness in AI Security
Ilias Tsingenopoulos
Vera Rimmer
Davy Preuveneers
Fabio Pierazzi
Lorenzo Cavallaro
Wouter Joosen
AAML
72
0
0
20 Dec 2023
Efficient Malware Analysis Using Metric Embeddings
Efficient Malware Analysis Using Metric Embeddings
Ethan M. Rudd
David B. Krisiloff
Scott E. Coull
Daniel Olszewski
Edward Raff
James Holt
AAML
25
6
0
05 Dec 2022
Multi-view Representation Learning from Malware to Defend Against
  Adversarial Variants
Multi-view Representation Learning from Malware to Defend Against Adversarial Variants
Junjie Hu
Mohammadreza Ebrahimi
Weifeng Li
Xin Li
Hsinchun Chen
AAML
18
2
0
25 Oct 2022
A Transferable and Automatic Tuning of Deep Reinforcement Learning for
  Cost Effective Phishing Detection
A Transferable and Automatic Tuning of Deep Reinforcement Learning for Cost Effective Phishing Detection
Orel Lavie
A. Shabtai
Gilad Katz
AAML
OffRL
27
1
0
19 Sep 2022
Fast & Furious: Modelling Malware Detection as Evolving Data Streams
Fast & Furious: Modelling Malware Detection as Evolving Data Streams
Fabrício Ceschin
Marcus Botacin
Heitor Murilo Gomes
Felipe Pinagé
Luiz S. Oliveira
André Grégio
AAML
9
17
0
24 May 2022
Stealing and Evading Malware Classifiers and Antivirus at Low False
  Positive Conditions
Stealing and Evading Malware Classifiers and Antivirus at Low False Positive Conditions
M. Rigaki
Sebastian Garcia
AAML
25
10
0
13 Apr 2022
StratDef: Strategic Defense Against Adversarial Attacks in ML-based
  Malware Detection
StratDef: Strategic Defense Against Adversarial Attacks in ML-based Malware Detection
Aqib Rashid
Jose Such
AAML
21
5
0
15 Feb 2022
On The Empirical Effectiveness of Unrealistic Adversarial Hardening
  Against Realistic Adversarial Attacks
On The Empirical Effectiveness of Unrealistic Adversarial Hardening Against Realistic Adversarial Attacks
Salijona Dyrmishi
Salah Ghamizi
Thibault Simonetto
Yves Le Traon
Maxime Cordy
AAML
26
16
0
07 Feb 2022
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
34
73
0
23 Dec 2021
Single-Shot Black-Box Adversarial Attacks Against Malware Detectors: A
  Causal Language Model Approach
Single-Shot Black-Box Adversarial Attacks Against Malware Detectors: A Causal Language Model Approach
Junjie Hu
Mohammadreza Ebrahimi
Hsinchun Chen
AAML
18
11
0
03 Dec 2021
A Comparison of State-of-the-Art Techniques for Generating Adversarial
  Malware Binaries
A Comparison of State-of-the-Art Techniques for Generating Adversarial Malware Binaries
P. Dasgupta
Zachary Osman
AAML
30
2
0
22 Nov 2021
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
35
51
0
07 Oct 2021
Why Adversarial Reprogramming Works, When It Fails, and How to Tell the
  Difference
Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference
Yang Zheng
Xiaoyi Feng
Zhaoqiang Xia
Xiaoyue Jiang
Ambra Demontis
Maura Pintor
Battista Biggio
Fabio Roli
AAML
25
21
0
26 Aug 2021
A survey on practical adversarial examples for malware classifiers
A survey on practical adversarial examples for malware classifiers
Daniel Park
B. Yener
AAML
36
14
0
06 Nov 2020
Generating End-to-End Adversarial Examples for Malware Classifiers Using
  Explainability
Generating End-to-End Adversarial Examples for Malware Classifiers Using Explainability
Ishai Rosenberg
Shai Meir
J. Berrebi
I. Gordon
Guillaume Sicard
Eli David
AAML
SILM
11
25
0
28 Sep 2020
MDEA: Malware Detection with Evolutionary Adversarial Learning
MDEA: Malware Detection with Evolutionary Adversarial Learning
Xiruo Wang
Risto Miikkulainen
AAML
19
15
0
09 Feb 2020
WAF-A-MoLE: Evading Web Application Firewalls through Adversarial
  Machine Learning
WAF-A-MoLE: Evading Web Application Firewalls through Adversarial Machine Learning
Luca Demetrio
Andrea Valenza
Gabriele Costa
Giovanni Lagorio
AAML
13
27
0
07 Jan 2020
Exploring Adversarial Examples in Malware Detection
Exploring Adversarial Examples in Malware Detection
Octavian Suciu
Scott E. Coull
Jeffrey Johns
AAML
23
188
0
18 Oct 2018
Applications of Graph Integration to Function Comparison and Malware
  Classification
Applications of Graph Integration to Function Comparison and Malware Classification
M. Slawinski
Andy Wortman
9
2
0
11 Oct 2018
1