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Exploring Adversarial Examples in Malware Detection

Exploring Adversarial Examples in Malware Detection

18 October 2018
Octavian Suciu
Scott E. Coull
Jeffrey Johns
    AAML
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Papers citing "Exploring Adversarial Examples in Malware Detection"

25 / 25 papers shown
Title
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive
  Attackers for Security Applications
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications
Hangsheng Zhang
Jiqiang Liu
Jinsong Dong
AAML
21
1
0
20 Jan 2024
High-resolution Image-based Malware Classification using Multiple
  Instance Learning
High-resolution Image-based Malware Classification using Multiple Instance Learning
Tim Peters
H. Farhat
14
0
0
21 Nov 2023
Madvex: Instrumentation-based Adversarial Attacks on Machine Learning
  Malware Detection
Madvex: Instrumentation-based Adversarial Attacks on Machine Learning Malware Detection
Yang Cai
Felix Mächtle
C. Daskalakis
Volodymyr Bezsmertnyi
T. Eisenbarth
AAML
31
7
0
04 May 2023
A Survey on Malware Detection with Graph Representation Learning
A Survey on Malware Detection with Graph Representation Learning
Tristan Bilot
Nour El Madhoun
Khaldoun Al Agha
Anis Zouaoui
AAML
13
20
0
28 Mar 2023
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers
  via Randomized Deletion
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion
Zhuoqun Huang
Neil G. Marchant
Keane Lucas
Lujo Bauer
O. Ohrimenko
Benjamin I. P. Rubinstein
AAML
29
15
0
31 Jan 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
23
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
J. Hu
Mohammadreza Ebrahimi
Weifeng Li
Xin Li
Hsinchun Chen
AAML
15
2
0
25 Oct 2022
Fusing Feature Engineering and Deep Learning: A Case Study for Malware
  Classification
Fusing Feature Engineering and Deep Learning: A Case Study for Malware Classification
Daniel Gibert
Carles Mateu
Jordi Planes
Quan Le
AAML
27
48
0
12 Jun 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
16
5
0
15 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
31
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
J. 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
28
2
0
22 Nov 2021
Who's Afraid of Thomas Bayes?
Who's Afraid of Thomas Bayes?
Erick Galinkin
AAML
25
0
0
30 Jul 2021
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
37
11
0
26 Apr 2021
Turning Federated Learning Systems Into Covert Channels
Turning Federated Learning Systems Into Covert Channels
Gabriele Costa
Fabio Pinelli
S. Soderi
Gabriele Tolomei
FedML
37
10
0
21 Apr 2021
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
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical
  Attacks on Machine Learning for Windows Malware Detection
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection
Luca Demetrio
Scott E. Coull
Battista Biggio
Giovanni Lagorio
A. Armando
Fabio Roli
AAML
22
59
0
17 Aug 2020
Functionality-preserving Black-box Optimization of Adversarial Windows
  Malware
Functionality-preserving Black-box Optimization of Adversarial Windows Malware
Luca Demetrio
Battista Biggio
Giovanni Lagorio
Fabio Roli
A. Armando
AAML
23
136
0
30 Mar 2020
Anomalous Example Detection in Deep Learning: A Survey
Anomalous Example Detection in Deep Learning: A Survey
Saikiran Bulusu
B. Kailkhura
Bo-wen Li
P. Varshney
D. Song
AAML
28
47
0
16 Mar 2020
Explanation-Guided Backdoor Poisoning Attacks Against Malware
  Classifiers
Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers
Giorgio Severi
J. Meyer
Scott E. Coull
Alina Oprea
AAML
SILM
21
18
0
02 Mar 2020
Malware Makeover: Breaking ML-based Static Analysis by Modifying
  Executable Bytes
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes
Keane Lucas
Mahmood Sharif
Lujo Bauer
Michael K. Reiter
S. Shintre
AAML
31
66
0
19 Dec 2019
The Threat of Adversarial Attacks on Machine Learning in Network
  Security -- A Survey
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey
Olakunle Ibitoye
Rana Abou-Khamis
Mohamed el Shehaby
Ashraf Matrawy
M. O. Shafiq
AAML
26
68
0
06 Nov 2019
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
Non-Negative Networks Against Adversarial Attacks
Non-Negative Networks Against Adversarial Attacks
William Fleshman
Edward Raff
Jared Sylvester
Steven Forsyth
Mark McLean
AAML
27
41
0
15 Jun 2018
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
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