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SNIFF: Reverse Engineering of Neural Networks with Fault Attacks
IEEE Transactions on Reliability (IEEE Trans. Reliab.), 2020
23 February 2020
J. Breier
Dirmanto Jap
Xiaolu Hou
S. Bhasin
Yang Liu
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Papers citing
"SNIFF: Reverse Engineering of Neural Networks with Fault Attacks"
49 / 49 papers shown
SoK: A Beginner-Friendly Introduction to Fault Injection Attacks
Christopher Simon Liu
Fan Wang
Patrick Gould
Carter Yagemann
62
0
0
22 Sep 2025
GATEBLEED: Exploiting On-Core Accelerator Power Gating for High Performance & Stealthy Attacks on AI
Joshua Kalyanapu
Farshad Dizani
Darsh Asher
Azam Ghanbari
Rosario Cammarota
Aydin Aysu
Samira Mirbagher Ajorpaz
360
0
0
22 Jul 2025
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments
Kaixiang Zhao
Lincan Li
Kaize Ding
Neil Zhenqiang Gong
Yue Zhao
Yushun Dong
AAML
288
7
0
22 Feb 2025
A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures
Shalini Saini
Anitha Chennamaneni
Babatunde Sawyerr
AAML
303
4
0
18 Dec 2024
A Survey on Failure Analysis and Fault Injection in AI Systems
Guangba Yu
Gou Tan
Haojia Huang
Zhenyu Zhang
Pengfei Chen
Roberto Natella
Zibin Zheng
328
18
0
28 Jun 2024
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent
Lorenz Kummer
Samir Moustafa
Nils N. Kriege
Wilfried N. Gansterer
GNN
AAML
233
0
0
02 Nov 2023
Privacy Side Channels in Machine Learning Systems
USENIX Security Symposium (USENIX Security), 2023
Edoardo Debenedetti
Giorgio Severi
Nicholas Carlini
Christopher A. Choquette-Choo
Matthew Jagielski
Milad Nasr
Eric Wallace
Florian Tramèr
MIALM
589
52
0
11 Sep 2023
A Desynchronization-Based Countermeasure Against Side-Channel Analysis of Neural Networks
International Conference on Cyber Security Cryptography and Machine Learning (ICCSCML), 2023
J. Breier
Dirmanto Jap
Xiaolu Hou
S. Bhasin
AAML
158
9
0
25 Mar 2023
A Practical Introduction to Side-Channel Extraction of Deep Neural Network Parameters
Smart Card Research and Advanced Application Conference (CARDIS), 2022
Raphael Joud
Pierre-Alain Moëllic
S. Pontié
J. Rigaud
AAML
MIACV
MLAU
224
15
0
10 Nov 2022
HWGN2: Side-channel Protected Neural Networks through Secure and Private Function Evaluation
Mohammad J. Hashemi
Steffi Roy
Domenic Forte
F. Ganji
AAML
208
3
0
07 Aug 2022
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences
ACM Computing Surveys (ACM CSUR), 2022
Daryna Oliynyk
Rudolf Mayer
Andreas Rauber
353
162
0
16 Jun 2022
Model Inversion Attack against Transfer Learning: Inverting a Model without Accessing It
Dayong Ye
Huiqiang Chen
Shuai Zhou
Tianqing Zhu
Wanlei Zhou
S. Ji
MIACV
203
8
0
13 Mar 2022
BDFA: A Blind Data Adversarial Bit-flip Attack on Deep Neural Networks
B. Ghavami
Mani Sadati
M. Shahidzadeh
Zhenman Fang
Lesley Shannon
AAML
272
3
0
07 Dec 2021
FooBaR: Fault Fooling Backdoor Attack on Neural Network Training
IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2021
J. Breier
Xiaolu Hou
Martín Ochoa
Jesus Solano
SILM
AAML
322
13
0
23 Sep 2021
Guarding Machine Learning Hardware Against Physical Side-Channel Attacks
ACM Journal on Emerging Technologies in Computing Systems (JETC), 2021
Anuj Dubey
Rosario Cammarota
Vikram B. Suresh
Aydin Aysu
AAML
275
39
0
01 Sep 2021
DeepFreeze: Cold Boot Attacks and High Fidelity Model Recovery on Commercial EdgeML Device
Yoo-Seung Won
Soham Chatterjee
Dirmanto Jap
A. Basu
S. Bhasin
AAML
FedML
167
14
0
03 Aug 2021
The Threat of Offensive AI to Organizations
Computers & security (CS), 2021
Yisroel Mirsky
Ambra Demontis
J. Kotak
Ram Shankar
Deng Gelei
Liu Yang
Xinming Zhang
Wenke Lee
Yuval Elovici
Battista Biggio
243
103
0
30 Jun 2021
A Review of Confidentiality Threats Against Embedded Neural Network Models
World Forum on Internet of Things (WF-IoT), 2021
Raphael Joud
Pierre-Alain Moëllic
Rémi Bernhard
J. Rigaud
196
6
0
04 May 2021
Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits
International Conference on Learning Representations (ICLR), 2021
Jiawang Bai
Baoyuan Wu
Yong Zhang
Yiming Li
Zhifeng Li
Shutao Xia
AAML
231
86
0
21 Feb 2021
Artificial Neural Networks and Fault Injection Attacks
Shahin Tajik
F. Ganji
SILM
267
14
0
17 Aug 2020
BoMaNet: Boolean Masking of an Entire Neural Network
Anuj Dubey
Rosario Cammarota
Aydin Aysu
AAML
214
57
0
16 Jun 2020
A Protection against the Extraction of Neural Network Models
International Conference on Information Systems Security and Privacy (ICISSP), 2020
H. Chabanne
Vincent Despiegel
Linda Guiga
FedML
176
5
0
26 May 2020
DeepHammer: Depleting the Intelligence of Deep Neural Networks through Targeted Chain of Bit Flips
USENIX Security Symposium (USENIX Security), 2020
Fan Yao
Adnan Siraj Rakin
Deliang Fan
AAML
191
203
0
30 Mar 2020
V0LTpwn: Attacking x86 Processor Integrity from Software
USENIX Security Symposium (USENIX Security), 2019
Zijo Kenjar
Tommaso Frassetto
David Gens
Michael Franz
A. Sadeghi
186
97
0
10 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Neural Information Processing Systems (NeurIPS), 2019
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
1.0K
50,197
0
03 Dec 2019
TBT: Targeted Neural Network Attack with Bit Trojan
Computer Vision and Pattern Recognition (CVPR), 2019
Adnan Siraj Rakin
Zhezhi He
Deliang Fan
AAML
411
251
0
10 Sep 2019
High Accuracy and High Fidelity Extraction of Neural Networks
USENIX Security Symposium (USENIX Security), 2019
Matthew Jagielski
Nicholas Carlini
David Berthelot
Alexey Kurakin
Nicolas Papernot
MLAU
MIACV
422
446
0
03 Sep 2019
SCNIFFER: Low-Cost, Automated, Efficient Electromagnetic Side-Channel Sniffing
IEEE Access (IEEE Access), 2019
Josef Danial
Debayan Das
Santosh K. Ghosh
A. Raychowdhury
Shreyas Sen
198
37
0
25 Aug 2019
Terminal Brain Damage: Exposing the Graceless Degradation in Deep Neural Networks Under Hardware Fault Attacks
USENIX Security Symposium (USENIX Security), 2019
Sanghyun Hong
Pietro Frigo
Yigitcan Kaya
Cristiano Giuffrida
Tudor Dumitras
AAML
180
245
0
03 Jun 2019
Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search
Adnan Siraj Rakin
Zhezhi He
Deliang Fan
AAML
243
286
0
28 Mar 2019
A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance
A. Shamir
Itay Safran
Eyal Ronen
O. Dunkelman
GAN
AAML
170
96
0
30 Jan 2019
Model Reconstruction from Model Explanations
S. Milli
Ludwig Schmidt
Anca Dragan
Moritz Hardt
FAtt
190
196
0
13 Jul 2018
Stealing Hyperparameters in Machine Learning
Binghui Wang
Neil Zhenqiang Gong
AAML
436
498
0
14 Feb 2018
Learning Transferable Architectures for Scalable Image Recognition
Barret Zoph
Vijay Vasudevan
Jonathon Shlens
Quoc V. Le
879
6,089
0
21 Jul 2017
Multiple Fault Attack on PRESENT with a Hardware Trojan Implementation in FPGA
International Workshop on Secure Internet of Things (SIoT), 2015
J. Breier
W. He
123
22
0
27 Feb 2017
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Zhuowen Tu
Kaiming He
1.2K
11,453
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16 Nov 2016
Membership Inference Attacks against Machine Learning Models
Reza Shokri
M. Stronati
Congzheng Song
Vitaly Shmatikov
SLR
MIALM
MIACV
928
4,966
0
18 Oct 2016
Xception: Deep Learning with Depthwise Separable Convolutions
Computer Vision and Pattern Recognition (CVPR), 2016
François Chollet
MDE
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PINN
3.5K
17,171
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07 Oct 2016
Stealing Machine Learning Models via Prediction APIs
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Fan Zhang
Ari Juels
Michael K. Reiter
Thomas Ristenpart
SILM
MLAU
462
2,044
0
09 Sep 2016
Densely Connected Convolutional Networks
Computer Vision and Pattern Recognition (CVPR), 2016
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
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Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
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Alexander A. Alemi
770
15,286
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23 Feb 2016
Deep Residual Learning for Image Recognition
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Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
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222,278
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10 Dec 2015
Rethinking the Inception Architecture for Computer Vision
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Resiliency of Deep Neural Networks under Quantization
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MQ
247
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20 Nov 2015
Explaining and Harnessing Adversarial Examples
International Conference on Learning Representations (ICLR), 2014
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Qualitatively characterizing neural network optimization problems
International Conference on Learning Representations (ICLR), 2014
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ODL
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558
0
19 Dec 2014
Going Deeper with Convolutions
Computer Vision and Pattern Recognition (CVPR), 2014
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Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
4.0K
46,738
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International Conference on Learning Representations (ICLR), 2014
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