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Cryptanalytic Extraction of Neural Network Models

Cryptanalytic Extraction of Neural Network Models

10 March 2020
Nicholas Carlini
Matthew Jagielski
Ilya Mironov
    FedML
    MLAU
    MIACV
    AAML
ArXivPDFHTML

Papers citing "Cryptanalytic Extraction of Neural Network Models"

25 / 25 papers shown
Title
Examining the Threat Landscape: Foundation Models and Model Stealing
Examining the Threat Landscape: Foundation Models and Model Stealing
Ankita Raj
Deepankar Varma
Chetan Arora
AAML
68
1
0
25 Feb 2025
Polynomial Time Cryptanalytic Extraction of Deep Neural Networks in the
  Hard-Label Setting
Polynomial Time Cryptanalytic Extraction of Deep Neural Networks in the Hard-Label Setting
Nicholas Carlini
J. Chávez-Saab
Anna Hambitzer
Francisco Rodríguez-Henríquez
Adi Shamir
AAML
20
1
0
08 Oct 2024
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
Boyang Zhang
Zheng Li
Ziqing Yang
Xinlei He
Michael Backes
Mario Fritz
Yang Zhang
21
4
0
19 Oct 2023
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing
  Inference Serving Systems
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems
Debopam Sanyal
Jui-Tse Hung
Manavi Agrawal
Prahlad Jasti
Shahab Nikkhoo
S. Jha
Tianhao Wang
Sibin Mohan
Alexey Tumanov
31
0
0
03 Jul 2023
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings
Asim Waheed
Vasisht Duddu
Nadarajah Asokan
32
9
0
17 Apr 2023
A Practical Introduction to Side-Channel Extraction of Deep Neural
  Network Parameters
A Practical Introduction to Side-Channel Extraction of Deep Neural Network Parameters
Raphael Joud
Pierre-Alain Moëllic
S. Pontié
J. Rigaud
AAML
MIACV
MLAU
19
13
0
10 Nov 2022
I Know What You Trained Last Summer: A Survey on Stealing Machine
  Learning Models and Defences
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences
Daryna Oliynyk
Rudolf Mayer
Andreas Rauber
29
106
0
16 Jun 2022
Reconstructing Training Data from Trained Neural Networks
Reconstructing Training Data from Trained Neural Networks
Niv Haim
Gal Vardi
Gilad Yehudai
Ohad Shamir
Michal Irani
27
132
0
15 Jun 2022
Local Identifiability of Deep ReLU Neural Networks: the Theory
Local Identifiability of Deep ReLU Neural Networks: the Theory
Joachim Bona-Pellissier
Franccois Malgouyres
F. Bachoc
FAtt
60
6
0
15 Jun 2022
Stealing and Evading Malware Classifiers and Antivirus at Low False
  Positive Conditions
Stealing and Evading Malware Classifiers and Antivirus at Low False Positive Conditions
M. Rigaki
Sebastian Garcia
AAML
20
10
0
13 Apr 2022
Fingerprinting Deep Neural Networks Globally via Universal Adversarial
  Perturbations
Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations
Zirui Peng
Shaofeng Li
Guoxing Chen
Cheng Zhang
Haojin Zhu
Minhui Xue
AAML
FedML
23
66
0
17 Feb 2022
Parameter identifiability of a deep feedforward ReLU neural network
Parameter identifiability of a deep feedforward ReLU neural network
Joachim Bona-Pellissier
François Bachoc
François Malgouyres
33
14
0
24 Dec 2021
Model Stealing Attacks Against Inductive Graph Neural Networks
Model Stealing Attacks Against Inductive Graph Neural Networks
Yun Shen
Xinlei He
Yufei Han
Yang Zhang
14
60
0
15 Dec 2021
TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep
  Neural Network Systems
TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems
Bao Gia Doan
Minhui Xue
Shiqing Ma
Ehsan Abbasnejad
D. Ranasinghe
AAML
28
53
0
19 Nov 2021
Efficiently Learning Any One Hidden Layer ReLU Network From Queries
Efficiently Learning Any One Hidden Layer ReLU Network From Queries
Sitan Chen
Adam R. Klivans
Raghu Meka
MLAU
MLT
37
8
0
08 Nov 2021
DeepSteal: Advanced Model Extractions Leveraging Efficient Weight
  Stealing in Memories
DeepSteal: Advanced Model Extractions Leveraging Efficient Weight Stealing in Memories
Adnan Siraj Rakin
Md Hafizul Islam Chowdhuryy
Fan Yao
Deliang Fan
AAML
MIACV
18
110
0
08 Nov 2021
SoK: Machine Learning Governance
SoK: Machine Learning Governance
Varun Chandrasekaran
Hengrui Jia
Anvith Thudi
Adelin Travers
Mohammad Yaghini
Nicolas Papernot
30
16
0
20 Sep 2021
Guarding Machine Learning Hardware Against Physical Side-Channel Attacks
Guarding Machine Learning Hardware Against Physical Side-Channel Attacks
Anuj Dubey
Rosario Cammarota
Vikram B. Suresh
Aydin Aysu
AAML
28
30
0
01 Sep 2021
SoK: How Robust is Image Classification Deep Neural Network
  Watermarking? (Extended Version)
SoK: How Robust is Image Classification Deep Neural Network Watermarking? (Extended Version)
Nils Lukas
Edward Jiang
Xinda Li
Florian Kerschbaum
AAML
28
86
0
11 Aug 2021
An Embedding of ReLU Networks and an Analysis of their Identifiability
An Embedding of ReLU Networks and an Analysis of their Identifiability
Pierre Stock
Rémi Gribonval
18
17
0
20 Jul 2021
The Trade-Offs of Private Prediction
The Trade-Offs of Private Prediction
L. V. D. van der Maaten
Awni Y. Hannun
10
22
0
09 Jul 2020
Stealing Deep Reinforcement Learning Models for Fun and Profit
Stealing Deep Reinforcement Learning Models for Fun and Profit
Kangjie Chen
Shangwei Guo
Tianwei Zhang
Xiaofei Xie
Yang Liu
MLAU
MIACV
OffRL
12
45
0
09 Jun 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
226
1,835
0
03 Feb 2017
Neural Architecture Search with Reinforcement Learning
Neural Architecture Search with Reinforcement Learning
Barret Zoph
Quoc V. Le
264
5,326
0
05 Nov 2016
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Z. Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
716
6,740
0
26 Sep 2016
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