ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1705.08131
  4. Cited By
Black-Box Attacks against RNN based Malware Detection Algorithms

Black-Box Attacks against RNN based Malware Detection Algorithms

23 May 2017
Weiwei Hu
Ying Tan
ArXiv (abs)PDFHTML

Papers citing "Black-Box Attacks against RNN based Malware Detection Algorithms"

23 / 23 papers shown
Title
Minerva: A File-Based Ransomware Detector
Minerva: A File-Based Ransomware Detector
Dorjan Hitaj
Giulio Pagnotta
Fabio De Gaspari
Lorenzo De Carli
L. Mancini
AAML
80
9
0
26 Jan 2023
Adversarial Feature Selection against Evasion Attacks
Adversarial Feature Selection against Evasion Attacks
Fei Zhang
P. Chan
Battista Biggio
D. Yeung
Fabio Roli
AAML
54
227
0
25 May 2020
Simple Black-Box Adversarial Perturbations for Deep Networks
Simple Black-Box Adversarial Perturbations for Deep Networks
Nina Narodytska
S. Kasiviswanathan
AAML
78
240
0
19 Dec 2016
Delving into Transferable Adversarial Examples and Black-box Attacks
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu
Xinyun Chen
Chang-rui Liu
Basel Alomair
AAML
143
1,741
0
08 Nov 2016
Categorical Reparameterization with Gumbel-Softmax
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
363
5,390
0
03 Nov 2016
Defensive Distillation is Not Robust to Adversarial Examples
Defensive Distillation is Not Robust to Adversarial Examples
Nicholas Carlini
D. Wagner
72
339
0
14 Jul 2016
Adversarial Perturbations Against Deep Neural Networks for Malware
  Classification
Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Kathrin Grosse
Nicolas Papernot
Praveen Manoharan
Michael Backes
Patrick McDaniel
AAML
87
418
0
14 Jun 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks
  using Adversarial Samples
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
SILMAAML
116
1,742
0
24 May 2016
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Nicolas Papernot
Patrick McDaniel
A. Swami
Richard E. Harang
AAMLGANSILM
61
456
0
28 Apr 2016
A General Retraining Framework for Scalable Adversarial Classification
A General Retraining Framework for Scalable Adversarial Classification
Bo Li
Yevgeniy Vorobeychik
Xinyun Chen
AAML
60
32
0
09 Apr 2016
Sequential Short-Text Classification with Recurrent and Convolutional
  Neural Networks
Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks
Ji Young Lee
Franck Dernoncourt
HAI
61
445
0
12 Mar 2016
Practical Black-Box Attacks against Machine Learning
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
S. Jha
Z. Berkay Celik
A. Swami
MLAUAAML
85
3,685
0
08 Feb 2016
The Limitations of Deep Learning in Adversarial Settings
The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot
Patrick McDaniel
S. Jha
Matt Fredrikson
Z. Berkay Celik
A. Swami
AAML
120
3,968
0
24 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep
  Neural Networks
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
Nicolas Papernot
Patrick McDaniel
Xi Wu
S. Jha
A. Swami
AAML
118
3,077
0
14 Nov 2015
Character-level Convolutional Networks for Text Classification
Character-level Convolutional Networks for Text Classification
Xiang Zhang
Jiaqi Zhao
Yann LeCun
270
6,135
0
04 Sep 2015
LSTM: A Search Space Odyssey
LSTM: A Search Space Odyssey
Klaus Greff
R. Srivastava
Jan Koutník
Bas R. Steunebrink
Jürgen Schmidhuber
AI4TSVLM
135
5,315
0
13 Mar 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual
  Attention
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Ke Xu
Jimmy Ba
Ryan Kiros
Kyunghyun Cho
Aaron Courville
Ruslan Salakhutdinov
R. Zemel
Yoshua Bengio
DiffM
350
10,083
0
10 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.1K
150,364
0
22 Dec 2014
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
282
19,129
0
20 Dec 2014
Sequence to Sequence Learning with Neural Networks
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever
Oriol Vinyals
Quoc V. Le
AIMat
448
20,606
0
10 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
578
27,338
0
01 Sep 2014
Learning Phrase Representations using RNN Encoder-Decoder for
  Statistical Machine Translation
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho
B. V. Merrienboer
Çağlar Gülçehre
Dzmitry Bahdanau
Fethi Bougares
Holger Schwenk
Yoshua Bengio
AIMat
1.1K
23,396
0
03 Jun 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
289
14,968
1
21 Dec 2013
1