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1909.01838
Cited By
High Accuracy and High Fidelity Extraction of Neural Networks
3 September 2019
Matthew Jagielski
Nicholas Carlini
David Berthelot
Alexey Kurakin
Nicolas Papernot
MLAU
MIACV
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Papers citing
"High Accuracy and High Fidelity Extraction of Neural Networks"
33 / 83 papers shown
Title
Defending against Model Stealing via Verifying Embedded External Features
Yiming Li
Linghui Zhu
Xiaojun Jia
Yong Jiang
Shutao Xia
Xiaochun Cao
AAML
37
61
0
07 Dec 2021
Property Inference Attacks Against GANs
Junhao Zhou
Yufei Chen
Chao Shen
Yang Zhang
AAML
MIACV
28
52
0
15 Nov 2021
Efficiently Learning Any One Hidden Layer ReLU Network From Queries
Sitan Chen
Adam R. Klivans
Raghu Meka
MLAU
MLT
42
8
0
08 Nov 2021
DeepSteal: Advanced Model Extractions Leveraging Efficient Weight Stealing in Memories
Adnan Siraj Rakin
Md Hafizul Islam Chowdhuryy
Fan Yao
Deliang Fan
AAML
MIACV
42
110
0
08 Nov 2021
Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective
Kha Dinh Duy
Taehyun Noh
Siwon Huh
Hojoon Lee
56
9
0
05 Nov 2021
SoK: Machine Learning Governance
Varun Chandrasekaran
Hengrui Jia
Anvith Thudi
Adelin Travers
Mohammad Yaghini
Nicolas Papernot
32
16
0
20 Sep 2021
Membership Inference Attacks Against Recommender Systems
Minxing Zhang
Z. Ren
Zihan Wang
Pengjie Ren
Zhumin Chen
Pengfei Hu
Yang Zhang
MIACV
AAML
18
83
0
16 Sep 2021
Guarding Machine Learning Hardware Against Physical Side-Channel Attacks
Anuj Dubey
Rosario Cammarota
Vikram B. Suresh
Aydin Aysu
AAML
30
30
0
01 Sep 2021
SoK: How Robust is Image Classification Deep Neural Network Watermarking? (Extended Version)
Nils Lukas
Edward Jiang
Xinda Li
Florian Kerschbaum
AAML
36
86
0
11 Aug 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
17
12
0
03 Aug 2021
MEGEX: Data-Free Model Extraction Attack against Gradient-Based Explainable AI
T. Miura
Satoshi Hasegawa
Toshiki Shibahara
SILM
MIACV
16
37
0
19 Jul 2021
Survey: Leakage and Privacy at Inference Time
Marija Jegorova
Chaitanya Kaul
Charlie Mayor
Alison Q. OÑeil
Alexander Weir
Roderick Murray-Smith
Sotirios A. Tsaftaris
PILM
MIACV
17
71
0
04 Jul 2021
HODA: Hardness-Oriented Detection of Model Extraction Attacks
A. M. Sadeghzadeh
Amir Mohammad Sobhanian
F. Dehghan
R. Jalili
MIACV
17
7
0
21 Jun 2021
A Review of Confidentiality Threats Against Embedded Neural Network Models
Raphael Joud
Pierre-Alain Moëllic
Rémi Bernhard
J. Rigaud
28
6
0
04 May 2021
Black-Box Dissector: Towards Erasing-based Hard-Label Model Stealing Attack
Yixu Wang
Jie Li
Hong Liu
Yan Wang
Yongjian Wu
Feiyue Huang
Rongrong Ji
AAML
22
34
0
03 May 2021
Proof-of-Learning: Definitions and Practice
Hengrui Jia
Mohammad Yaghini
Christopher A. Choquette-Choo
Natalie Dullerud
Anvith Thudi
Varun Chandrasekaran
Nicolas Papernot
AAML
20
98
0
09 Mar 2021
Membership Inference Attacks are Easier on Difficult Problems
Avital Shafran
Shmuel Peleg
Yedid Hoshen
MIACV
11
16
0
15 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning
Xinlei He
Yang Zhang
11
51
0
08 Feb 2021
Data-Free Model Extraction
Jean-Baptiste Truong
Pratyush Maini
R. Walls
Nicolas Papernot
MIACV
15
181
0
30 Nov 2020
Amnesiac Machine Learning
Laura Graves
Vineel Nagisetty
Vijay Ganesh
MU
MIACV
16
242
0
21 Oct 2020
Model extraction from counterfactual explanations
Ulrich Aivodji
Alexandre Bolot
Sébastien Gambs
MIACV
MLAU
27
51
0
03 Sep 2020
A Survey of Privacy Attacks in Machine Learning
M. Rigaki
Sebastian Garcia
PILM
AAML
27
213
0
15 Jul 2020
SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems
H. Abdullah
Kevin Warren
Vincent Bindschaedler
Nicolas Papernot
Patrick Traynor
AAML
24
128
0
13 Jul 2020
Improving LIME Robustness with Smarter Locality Sampling
Sean Saito
Eugene Chua
Nicholas Capel
Rocco Hu
FAtt
AAML
7
22
0
22 Jun 2020
Stealing Deep Reinforcement Learning Models for Fun and Profit
Kangjie Chen
Shangwei Guo
Tianwei Zhang
Xiaofei Xie
Yang Liu
MLAU
MIACV
OffRL
14
45
0
09 Jun 2020
Perturbing Inputs to Prevent Model Stealing
J. Grana
AAML
SILM
11
5
0
12 May 2020
SNIFF: Reverse Engineering of Neural Networks with Fault Attacks
J. Breier
Dirmanto Jap
Xiaolu Hou
S. Bhasin
Yang Liu
15
52
0
23 Feb 2020
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps
Zhichuang Sun
Ruimin Sun
Long Lu
Alan Mislove
31
78
0
18 Feb 2020
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas
Yuxuan Zhang
Florian Kerschbaum
MLAU
FedML
AAML
31
144
0
02 Dec 2019
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
Extraction of Complex DNN Models: Real Threat or Boogeyman?
B. Atli
S. Szyller
Mika Juuti
Samuel Marchal
Nadarajah Asokan
MLAU
MIACV
25
45
0
11 Oct 2019
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
228
1,835
0
03 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
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