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NAttack! Adversarial Attacks to bypass a GAN based classifier trained to
  detect Network intrusion

NAttack! Adversarial Attacks to bypass a GAN based classifier trained to detect Network intrusion

20 February 2020
Aritran Piplai
Sai Sree Laya Chukkapalli
A. Joshi
    GAN
    AAML
ArXivPDFHTML

Papers citing "NAttack! Adversarial Attacks to bypass a GAN based classifier trained to detect Network intrusion"

4 / 4 papers shown
Title
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Han Xu
Yao Ma
Haochen Liu
Debayan Deb
Hui Liu
Jiliang Tang
Anil K. Jain
AAML
67
675
0
17 Sep 2019
Detecting egregious responses in neural sequence-to-sequence models
Detecting egregious responses in neural sequence-to-sequence models
Tianxing He
James R. Glass
AAML
56
22
0
11 Sep 2018
Robust Physical-World Attacks on Deep Learning Models
Robust Physical-World Attacks on Deep Learning Models
Kevin Eykholt
Ivan Evtimov
Earlence Fernandes
Yue Liu
Amir Rahmati
Chaowei Xiao
Atul Prakash
Tadayoshi Kohno
D. Song
AAML
54
595
0
27 Jul 2017
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
277
19,066
0
20 Dec 2014
1