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How to 0wn NAS in Your Spare Time
v1v2 (latest)

How to 0wn NAS in Your Spare Time

17 February 2020
Sanghyun Hong
Michael Davinroy
Yigitcan Kaya
Dana Dachman-Soled
Tudor Dumitras
ArXiv (abs)PDFHTML

Papers citing "How to 0wn NAS in Your Spare Time"

17 / 17 papers shown
A Semi Black-Box Adversarial Bit-Flip Attack with Limited DNN Model
  Information
A Semi Black-Box Adversarial Bit-Flip Attack with Limited DNN Model InformationICCD (ICCD), 2024
B. Ghavami
Mani Sadati
M. Shahidzadeh
Lesley Shannon
S. Wilton
AAML
251
2
0
12 Dec 2024
What Was Your Prompt? A Remote Keylogging Attack on AI Assistants
What Was Your Prompt? A Remote Keylogging Attack on AI AssistantsUSENIX Security Symposium (USENIX Security), 2024
Roy Weiss
Daniel Ayzenshteyn
Guy Amit
Yisroel Mirsky
320
27
0
14 Mar 2024
Army of Thieves: Enhancing Black-Box Model Extraction via Ensemble based
  sample selection
Army of Thieves: Enhancing Black-Box Model Extraction via Ensemble based sample selection
Akshit Jindal
Vikram Goyal
Saket Anand
Chetan Arora
FedML
309
5
0
08 Nov 2023
Mercury: An Automated Remote Side-channel Attack to Nvidia Deep Learning
  Accelerator
Mercury: An Automated Remote Side-channel Attack to Nvidia Deep Learning AcceleratorInternational Conference on Field-Programmable Technology (ICFPT), 2023
Xi-ai Yan
Xiaoxuan Lou
Guowen Xu
Han Qiu
Shangwei Guo
Chip Hong Chang
Tianwei Zhang
AAML
166
13
0
02 Aug 2023
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
295
12
0
08 Sep 2022
Demystifying Arch-hints for Model Extraction: An Attack in Unified
  Memory System
Demystifying Arch-hints for Model Extraction: An Attack in Unified Memory System
Zhendong Wang
Xiaoming Zeng
Xulong Tang
Qiang Yan
Xingbo Hu
Yang Hu
AAMLMIACVFedML
194
7
0
29 Aug 2022
Careful What You Wish For: on the Extraction of Adversarially Trained
  Models
Careful What You Wish For: on the Extraction of Adversarially Trained ModelsConference on Privacy, Security and Trust (PST), 2022
Kacem Khaled
Gabriela Nicolescu
F. Magalhães
MIACVAAML
208
7
0
21 Jul 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
385
165
0
16 Jun 2022
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
AAMLMIACV
246
159
0
08 Nov 2021
On the Security Risks of AutoML
On the Security Risks of AutoMLUSENIX Security Symposium (USENIX Security), 2021
Ren Pang
Zhaohan Xi
S. Ji
Xiapu Luo
Ting Wang
AAML
280
16
0
12 Oct 2021
Can one hear the shape of a neural network?: Snooping the GPU via
  Magnetic Side Channel
Can one hear the shape of a neural network?: Snooping the GPU via Magnetic Side Channel
H. Maia
Chang Xiao
Dingzeyu Li
E. Grinspun
Changxi Zheng
AAML
266
34
0
15 Sep 2021
Ownership Verification of DNN Architectures via Hardware Cache Side
  Channels
Ownership Verification of DNN Architectures via Hardware Cache Side Channels
Xiaoxuan Lou
Shangwei Guo
Jiwei Li
Tianwei Zhang
288
14
0
06 Feb 2021
Database Reconstruction from Noisy Volumes: A Cache Side-Channel Attack
  on SQLite
Database Reconstruction from Noisy Volumes: A Cache Side-Channel Attack on SQLite
Aria Shahverdi
M. Shirinov
Dana Dachman-Soled
AAML
198
20
0
26 Jun 2020
De-Anonymizing Text by Fingerprinting Language Generation
De-Anonymizing Text by Fingerprinting Language Generation
Zhen Sun
R. Schuster
Vitaly Shmatikov
319
7
0
17 Jun 2020
A Protection against the Extraction of Neural Network Models
A Protection against the Extraction of Neural Network ModelsInternational Conference on Information Systems Security and Privacy (ICISSP), 2020
H. Chabanne
Vincent Despiegel
Linda Guiga
FedML
214
5
0
26 May 2020
Cryptanalytic Extraction of Neural Network Models
Cryptanalytic Extraction of Neural Network ModelsAnnual International Cryptology Conference (CRYPTO), 2020
Nicholas Carlini
Matthew Jagielski
Ilya Mironov
FedMLMLAUMIACVAAML
519
156
0
10 Mar 2020
Quantifying (Hyper) Parameter Leakage in Machine Learning
Quantifying (Hyper) Parameter Leakage in Machine LearningIEEE International Conference on Multimedia Big Data (ICMBD), 2019
Vasisht Duddu
D. V. Rao
AAMLMIACVFedML
176
6
0
31 Oct 2019
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