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Constrained Network Adversarial Attacks: Validity, Robustness, and Transferability

Constrained Network Adversarial Attacks: Validity, Robustness, and Transferability

2 May 2025
Anass Grini
Oumaima Taheri
Btissam El Khamlichi
Amal El Fallah-Seghrouchni
    AAML
ArXiv (abs)PDFHTML

Papers citing "Constrained Network Adversarial Attacks: Validity, Robustness, and Transferability"

11 / 11 papers shown
Title
HPAC-IDS: A Hierarchical Packet Attention Convolution for Intrusion Detection System
HPAC-IDS: A Hierarchical Packet Attention Convolution for Intrusion Detection System
Anass Grini
Btissam El Khamlichi
Abdellatif El Afia
Amal El Fallah-Seghrouchni
124
1
0
09 Jan 2025
Adversarial Examples in Constrained Domains
Adversarial Examples in Constrained Domains
Ryan Sheatsley
Nicolas Papernot
Mike Weisman
Gunjan Verma
Patrick McDaniel
AAML
59
24
0
02 Nov 2020
Adversarial Machine Learning in Network Intrusion Detection Systems
Adversarial Machine Learning in Network Intrusion Detection Systems
Elie Alhajjar
P. Maxwell
Nathaniel D. Bastian
GANSILMAAML
95
140
0
23 Apr 2020
IDSGAN: Generative Adversarial Networks for Attack Generation against
  Intrusion Detection
IDSGAN: Generative Adversarial Networks for Attack Generation against Intrusion Detection
Zilong Lin
Yong-yu Shi
Zhi Xue
AAML
56
266
0
06 Sep 2018
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural
  Networks without Training Substitute Models
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models
Pin-Yu Chen
Huan Zhang
Yash Sharma
Jinfeng Yi
Cho-Jui Hsieh
AAML
87
1,885
0
14 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILMOOD
319
12,138
0
19 Jun 2017
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
472
3,148
0
04 Nov 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
282
8,587
0
16 Aug 2016
DeepFool: a simple and accurate method to fool deep neural networks
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
154
4,905
0
14 Nov 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
282
19,129
0
20 Dec 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
286
14,968
1
21 Dec 2013
1