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Cryptanalytic Extraction of Neural Network Models
v1v2 (latest)

Cryptanalytic Extraction of Neural Network Models

Annual International Cryptology Conference (CRYPTO), 2020
10 March 2020
Nicholas Carlini
Matthew Jagielski
Ilya Mironov
    FedMLMLAUMIACVAAML
ArXiv (abs)PDFHTMLGithub (50★)

Papers citing "Cryptanalytic Extraction of Neural Network Models"

50 / 100 papers shown
Is the Hard-Label Cryptanalytic Model Extraction Really Polynomial?
Is the Hard-Label Cryptanalytic Model Extraction Really Polynomial?
Akira Ito
Takayuki Miura
Yosuke Todo
AAMLMIACVMLAU
348
5
0
30 Mar 2026
Data Augmentation Techniques to Reverse-Engineer Neural Network Weights from Input-Output Queries
Data Augmentation Techniques to Reverse-Engineer Neural Network Weights from Input-Output Queries
Alexander Beiser
Flavio Martinelli
W. Gerstner
Johanni Brea
254
0
0
25 Nov 2025
AttackPilot: Autonomous Inference Attacks Against ML Services With LLM-Based Agents
AttackPilot: Autonomous Inference Attacks Against ML Services With LLM-Based Agents
Yixin Wu
Rui Wen
Chi Cui
Michael Backes
Yang Zhang
AAML
241
2
0
24 Nov 2025
Cryptographic Backdoor for Neural Networks: Boon and Bane
Cryptographic Backdoor for Neural Networks: Boon and Bane
Anh Tu Ngo
Anupam Chattopadhyay
Subhamoy Maitra
AAML
170
0
0
25 Sep 2025
Train to Defend: First Defense Against Cryptanalytic Neural Network Parameter Extraction Attacks
Train to Defend: First Defense Against Cryptanalytic Neural Network Parameter Extraction Attacks
Ashley Kurian
Aydin Aysu
AAML
143
0
0
20 Sep 2025
Delving into Cryptanalytic Extraction of PReLU Neural Networks
Delving into Cryptanalytic Extraction of PReLU Neural Networks
Yi Chen
Xiaoyang Dong
Ruijie Ma
Yantian Shen
Anyu Wang
Hongbo Yu
Xiaoyun Wang
AAML
165
4
0
20 Sep 2025
GATEBLEED: Exploiting On-Core Accelerator Power Gating for High Performance & Stealthy Attacks on AI
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
396
0
0
22 Jul 2025
AICrypto: Evaluating Cryptography Capabilities of Large Language Models
AICrypto: Evaluating Cryptography Capabilities of Large Language Models
Yu Wang
Y. Liu
Liheng Ji
Han Luo
Wenjie Li
...
Geyuan Zhang
X. Li
Rongwu Xu
Yilei Chen
Tianxing He
ELM
468
3
0
13 Jul 2025
Navigating the Deep: End-to-End Extraction on Deep Neural Networks
Navigating the Deep: End-to-End Extraction on Deep Neural Networks
Haolin Liu
Adrien Siproudhis
Samuel Experton
Peter Lorenz
Christina Boura
Thomas Peyrin
AAML
256
2
0
20 Jun 2025
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
636
3
0
25 Feb 2025
A Divide-and-Conquer Strategy for Hard-Label Extraction of Deep Neural Networks via Side-Channel Attacks
A Divide-and-Conquer Strategy for Hard-Label Extraction of Deep Neural Networks via Side-Channel AttacksIACR Cryptology ePrint Archive (IACR ePrint), 2024
Benoît Coqueret
Mathieu Carbone
Olivier Sentieys
Gabriel Zaid
AAMLMLAUFedML
331
3
0
15 Nov 2024
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 SettingIACR Cryptology ePrint Archive (IACR ePrint), 2024
Nicholas Carlini
J. Chávez-Saab
Anna Hambitzer
Francisco Rodríguez-Henríquez
Adi Shamir
AAML
258
23
0
08 Oct 2024
Understanding Data Importance in Machine Learning Attacks: Does Valuable
  Data Pose Greater Harm?
Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?Network and Distributed System Security Symposium (NDSS), 2024
Rui Wen
Michael Backes
Yang Zhang
TDIAAML
288
5
0
05 Sep 2024
Beyond Slow Signs in High-fidelity Model Extraction
Beyond Slow Signs in High-fidelity Model ExtractionNeural Information Processing Systems (NeurIPS), 2024
Hanna Foerster
Robert D. Mullins
Ilia Shumailov
Jamie Hayes
AAML
403
12
0
14 Jun 2024
AI Risk Management Should Incorporate Both Safety and Security
AI Risk Management Should Incorporate Both Safety and Security
Xiangyu Qi
Yangsibo Huang
Yi Zeng
Edoardo Debenedetti
Jonas Geiping
...
Chaowei Xiao
Yue Liu
Dawn Song
Peter Henderson
Prateek Mittal
AAML
320
21
0
29 May 2024
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
Shanglun Feng
Florian Tramèr
SILM
302
31
0
30 Mar 2024
Stealing Part of a Production Language Model
Stealing Part of a Production Language ModelInternational Conference on Machine Learning (ICML), 2024
Nicholas Carlini
Daniel Paleka
Krishnamurthy Dvijotham
Thomas Steinke
Jonathan Hayase
...
Arthur Conmy
Itay Yona
Eric Wallace
David Rolnick
Florian Tramèr
MLAUAAML
398
154
0
11 Mar 2024
Amplifying Training Data Exposure through Fine-Tuning with
  Pseudo-Labeled Memberships
Amplifying Training Data Exposure through Fine-Tuning with Pseudo-Labeled Memberships
Myung Gyo Oh
Hong Eun Ahn
L. Park
T.-H. Kwon
MIALMAAML
375
0
0
19 Feb 2024
Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey
  and the Open Libraries Behind Them
Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them
Chao-Jung Liu
Boxi Chen
Wei Shao
Chris Zhang
Kelvin Wong
Yi Zhang
410
7
0
22 Jan 2024
Reverse Engineering Deep ReLU Networks An Optimization-based Algorithm
Reverse Engineering Deep ReLU Networks An Optimization-based Algorithm
Mehrab Hamidi
322
0
0
07 Dec 2023
Like an Open Book? Read Neural Network Architecture with Simple Power
  Analysis on 32-bit Microcontrollers
Like an Open Book? Read Neural Network Architecture with Simple Power Analysis on 32-bit MicrocontrollersSmart Card Research and Advanced Application Conference (CARDIS), 2023
Raphael Joud
Pierre-Alain Moëllic
S. Pontié
J. Rigaud
361
5
0
02 Nov 2023
MIST: Defending Against Membership Inference Attacks Through
  Membership-Invariant Subspace Training
MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace TrainingUSENIX Security Symposium (USENIX Security), 2023
Jiacheng Li
Ninghui Li
Bruno Ribeiro
405
15
0
02 Nov 2023
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
372
10
0
19 Oct 2023
Polynomial Time Cryptanalytic Extraction of Neural Network Models
Polynomial Time Cryptanalytic Extraction of Neural Network ModelsIACR Cryptology ePrint Archive (IACR ePrint), 2023
Adi Shamir
Isaac Canales-Martínez
Anna Hambitzer
J. Chávez-Saab
Francisco Rodríguez-Henríquez
Nitin Satpute
AAMLMLAU
363
28
0
12 Oct 2023
Beyond Labeling Oracles: What does it mean to steal ML models?
Beyond Labeling Oracles: What does it mean to steal ML models?
Avital Shafran
Ilia Shumailov
Murat A. Erdogdu
Nicolas Papernot
AAML
423
5
0
03 Oct 2023
DeepTheft: Stealing DNN Model Architectures through Power Side Channel
DeepTheft: Stealing DNN Model Architectures through Power Side ChannelIEEE Symposium on Security and Privacy (IEEE S&P), 2023
Yansong Gao
Huming Qiu
Zhi-Li Zhang
Binghui Wang
Hua Ma
A. Abuadbba
Minhui Xue
Anmin Fu
Surya Nepal
MLAUFedML
219
35
0
21 Sep 2023
Fault Injection and Safe-Error Attack for Extraction of Embedded Neural
  Network Models
Fault Injection and Safe-Error Attack for Extraction of Embedded Neural Network Models
Kevin Hector
Pierre-Alain Moëllic
Mathieu Dumont
J. Dutertre
SILMMIACV
355
6
0
31 Aug 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
439
1
0
03 Jul 2023
Hidden symmetries of ReLU networks
Hidden symmetries of ReLU networksInternational Conference on Machine Learning (ICML), 2023
J. E. Grigsby
Kathryn A. Lindsey
David Rolnick
353
32
0
09 Jun 2023
Expand-and-Cluster: Parameter Recovery of Neural Networks
Expand-and-Cluster: Parameter Recovery of Neural NetworksInternational Conference on Machine Learning (ICML), 2023
Flavio Martinelli
Berfin Simsek
W. Gerstner
Johanni Brea
618
15
0
25 Apr 2023
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings
GrOVe: Ownership Verification of Graph Neural Networks using EmbeddingsIEEE Symposium on Security and Privacy (IEEE S&P), 2023
Asim Waheed
Vasisht Duddu
Nadarajah Asokan
368
19
0
17 Apr 2023
False Claims against Model Ownership Resolution
False Claims against Model Ownership ResolutionUSENIX Security Symposium (USENIX Security), 2023
Jian Liu
Rui Zhang
S. Szyller
Kui Ren
Nirmal Asokan
AAMLMLAU
844
21
0
13 Apr 2023
EZClone: Improving DNN Model Extraction Attack via Shape Distillation
  from GPU Execution Profiles
EZClone: Improving DNN Model Extraction Attack via Shape Distillation from GPU Execution Profiles
Jonah O'Brien Weiss
Tiago A. O. Alves
S. Kundu
MIACVAAMLFedML
237
8
0
06 Apr 2023
A Plot is Worth a Thousand Words: Model Information Stealing Attacks via
  Scientific Plots
A Plot is Worth a Thousand Words: Model Information Stealing Attacks via Scientific PlotsUSENIX Security Symposium (USENIX Security), 2023
Boyang Zhang
Xinlei He
Yun Shen
Tianhao Wang
Yang Zhang
AAML
300
6
0
23 Feb 2023
TT-TFHE: a Torus Fully Homomorphic Encryption-Friendly Neural Network Architecture
TT-TFHE: a Torus Fully Homomorphic Encryption-Friendly Neural Network Architecture
Adrien Benamira
Tristan Guérand
Thomas Peyrin
Sayandeep Saha
344
8
0
03 Feb 2023
Feature-Space Bayesian Adversarial Learning Improved Malware Detector
  Robustness
Feature-Space Bayesian Adversarial Learning Improved Malware Detector RobustnessAAAI Conference on Artificial Intelligence (AAAI), 2023
Bao Gia Doan
Shuiqiao Yang
Paul Montague
O. Vel
Tamas Abraham
S. Çamtepe
S. Kanhere
Ehsan Abbasnejad
Damith C. Ranasinghe
OODAAML
267
10
0
30 Jan 2023
A Practical Introduction to Side-Channel Extraction of Deep Neural
  Network Parameters
A Practical Introduction to Side-Channel Extraction of Deep Neural Network ParametersSmart Card Research and Advanced Application Conference (CARDIS), 2022
Raphael Joud
Pierre-Alain Moëllic
S. Pontié
J. Rigaud
AAMLMIACVMLAU
269
16
0
10 Nov 2022
Preprocessors Matter! Realistic Decision-Based Attacks on Machine
  Learning Systems
Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning SystemsInternational Conference on Machine Learning (ICML), 2022
Chawin Sitawarin
Florian Tramèr
Nicholas Carlini
AAML
302
10
0
07 Oct 2022
SEEK: model extraction attack against hybrid secure inference protocols
SEEK: model extraction attack against hybrid secure inference protocolsIACR Cryptology ePrint Archive (IACR ePrint), 2022
Si-Quan Chen
Junfeng Fan
MIACV
243
2
0
14 Sep 2022
Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future
  Directions
Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions
Chulin Xie
Zhong Cao
Yunhui Long
Diange Yang
Ding Zhao
Yue Liu
296
12
0
08 Sep 2022
HWGN2: Side-channel Protected Neural Networks through Secure and Private
  Function Evaluation
HWGN2: Side-channel Protected Neural Networks through Secure and Private Function Evaluation
Mohammad J. Hashemi
Steffi Roy
Domenic Forte
F. Ganji
AAML
263
3
0
07 Aug 2022
Conflicting Interactions Among Protection Mechanisms for Machine
  Learning Models
Conflicting Interactions Among Protection Mechanisms for Machine Learning ModelsAAAI Conference on Artificial Intelligence (AAAI), 2022
S. Szyller
Nadarajah Asokan
AAML
436
13
0
05 Jul 2022
Matryoshka: Stealing Functionality of Private ML Data by Hiding Models
  in Model
Matryoshka: Stealing Functionality of Private ML Data by Hiding Models in Model
Xudong Pan
Yifan Yan
Sheng Zhang
Mi Zhang
Min Yang
295
1
0
29 Jun 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 DefencesACM Computing Surveys (ACM CSUR), 2022
Daryna Oliynyk
Rudolf Mayer
Andreas Rauber
396
167
0
16 Jun 2022
Reconstructing Training Data from Trained Neural Networks
Reconstructing Training Data from Trained Neural NetworksNeural Information Processing Systems (NeurIPS), 2022
Niv Haim
Gal Vardi
Gilad Yehudai
Ohad Shamir
Michal Irani
381
175
0
15 Jun 2022
Local Identifiability of Deep ReLU Neural Networks: the Theory
Local Identifiability of Deep ReLU Neural Networks: the TheoryNeural Information Processing Systems (NeurIPS), 2022
Joachim Bona-Pellissier
Franccois Malgouyres
François Bachoc
FAtt
410
12
0
15 Jun 2022
Fusion: Efficient and Secure Inference Resilient to Malicious Servers
Fusion: Efficient and Secure Inference Resilient to Malicious ServersNetwork and Distributed System Security Symposium (NDSS), 2022
Caiqin Dong
Jian Weng
Jia-Nan Liu
Yue Zhang
Yao Tong
Anjia Yang
Yudan Cheng
Shun Hu
452
22
0
06 May 2022
One Picture is Worth a Thousand Words: A New Wallet Recovery Process
One Picture is Worth a Thousand Words: A New Wallet Recovery ProcessGlobal Communications Conference (GLOBECOM), 2022
H. Chabanne
Vincent Despiegel
Linda Guiga
320
0
0
05 May 2022
Stealing and Evading Malware Classifiers and Antivirus at Low False
  Positive Conditions
Stealing and Evading Malware Classifiers and Antivirus at Low False Positive ConditionsComputers & security (Comput. Secur.), 2022
M. Rigaki
Sebastian Garcia
AAML
343
12
0
13 Apr 2022
Split HE: Fast Secure Inference Combining Split Learning and Homomorphic
  Encryption
Split HE: Fast Secure Inference Combining Split Learning and Homomorphic Encryption
George-Liviu Pereteanu
A. Alansary
Jonathan Passerat-Palmbach
FedML
250
27
0
27 Feb 2022
12
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