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Towards the Science of Security and Privacy in Machine Learning

Towards the Science of Security and Privacy in Machine Learning

11 November 2016
Nicolas Papernot
Patrick McDaniel
Arunesh Sinha
Michael P. Wellman
    AAML
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Papers citing "Towards the Science of Security and Privacy in Machine Learning"

12 / 12 papers shown
Title
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices
Han Zhang
Zifan Wang
Mihir Dhamankar
Matt Fredrikson
Yuvraj Agarwal
71
2
0
02 Jun 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Sheng Liu
Zihan Wang
Yuxiao Chen
Qi Lei
AAML
MIACV
65
4
0
13 Feb 2024
Runtime Stealthy Perception Attacks against DNN-based Adaptive Cruise Control Systems
Runtime Stealthy Perception Attacks against DNN-based Adaptive Cruise Control Systems
Xugui Zhou
Anqi Chen
Maxfield Kouzel
Haotian Ren
Morgan McCarty
Cristina Nita-Rotaru
H. Alemzadeh
AAML
41
2
0
18 Jul 2023
Evasion Attacks against Machine Learning at Test Time
Evasion Attacks against Machine Learning at Test Time
Battista Biggio
Igino Corona
Davide Maiorca
B. Nelson
Nedim Srndic
Pavel Laskov
Giorgio Giacinto
Fabio Roli
AAML
90
2,140
0
21 Aug 2017
Membership Inference Attacks against Machine Learning Models
Membership Inference Attacks against Machine Learning Models
Reza Shokri
M. Stronati
Congzheng Song
Vitaly Shmatikov
SLR
MIALM
MIACV
200
4,075
0
18 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon M. Kleinberg
S. Mullainathan
Manish Raghavan
FaML
79
1,762
0
19 Sep 2016
Adversarial Perturbations Against Deep Neural Networks for Malware
  Classification
Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Kathrin Grosse
Nicolas Papernot
Praveen Manoharan
Michael Backes
Patrick McDaniel
AAML
35
418
0
14 Jun 2016
A Unified Gradient Regularization Family for Adversarial Examples
A Unified Gradient Regularization Family for Adversarial Examples
Chunchuan Lyu
Kaizhu Huang
Hai-Ning Liang
AAML
37
207
0
19 Nov 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
Ulfar Erlingsson
Vasyl Pihur
Aleksandra Korolova
48
1,977
0
25 Jul 2014
Poisoning Attacks against Support Vector Machines
Poisoning Attacks against Support Vector Machines
Battista Biggio
B. Nelson
Pavel Laskov
AAML
74
1,580
0
27 Jun 2012
Noise Tolerance under Risk Minimization
Noise Tolerance under Risk Minimization
Naresh Manwani
S. M. I. P. S. Sastry
NoLa
92
273
0
24 Sep 2011
Query Strategies for Evading Convex-Inducing Classifiers
Query Strategies for Evading Convex-Inducing Classifiers
B. Nelson
Benjamin I. P. Rubinstein
Ling Huang
A. Joseph
Steven J. Lee
Satish Rao
J. D. Tygar
69
124
0
03 Jul 2010
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