Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification

30 December 2022

Pedro Miguel Sánchez Sánchez

Alberto Huertas Celdrán

Gérome Bovet

Gregorio Martínez Pérez

AAML

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Papers citing "Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification"

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Title
DRAWNAPART: A Device Identification Technique based on Remote GPU Fingerprinting Tomer Laor Naif Mehanna Antonin Durey Vitaly Dyadyuk Pierre Laperdrix Clémentine Maurice Yossi Oren Romain Rouvoy Walter Rudametkin U. Adelaide MLAU 40 34 0 24 Jan 2022
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems Giovanni Apruzzese M. Andreolini Luca Ferretti Mirco Marchetti M. Colajanni AAML 64 106 0 17 Jun 2021
A methodology to identify identical single-board computers based on hardware behavior fingerprinting Pedro Miguel Sánchez Sánchez José María Jorquera Valero Alberto Huertas Celdrán Gérome Bovet M. Gil Pérez Gregorio Martínez Pérez 34 10 0 15 Jun 2021
Machine Learning for the Detection and Identification of Internet of Things (IoT) Devices: A Survey Yongxin Liu Jian Wang Jianqiang Li Shuteng Niu Haoze Song 74 133 0 25 Jan 2021
Adversarial Attacks on Deep Learning Systems for User Identification based on Motion Sensors Cezara Benegui Radu Tudor Ionescu AAML 28 9 0 02 Sep 2020
A Survey on Device Behavior Fingerprinting: Data Sources, Techniques, Application Scenarios, and Datasets Pedro Miguel Sánchez Sánchez José María Jorquera Valero Alberto Huertas Celdrán Gérome Bovet M. Pérez Gregorio Martínez Pérez 47 96 0 07 Aug 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 134 1,175 0 12 Jan 2020
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 64 69 0 06 Nov 2019
Interpreting and Evaluating Neural Network Robustness Fuxun Yu Zhuwei Qin Chenchen Liu Liang Zhao Yanzhi Wang Xiang Chen AAML 27 55 0 10 May 2019
1D Convolutional Neural Networks and Applications: A Survey S. Kiranyaz Onur Avcı Osama Abdeljaber T. Ince Moncef Gabbouj D. Inman 3DV 58 1,913 0 09 May 2019
Adversarial Robustness Toolbox v1.0.0 Maria-Irina Nicolae M. Sinn Minh-Ngoc Tran Beat Buesser Ambrish Rawat ... Nathalie Baracaldo Bryant Chen Heiko Ludwig Ian Molloy Ben Edwards AAML VLM 72 458 0 03 Jul 2018
Privacy Preserving Machine Learning: Threats and Solutions Mohammad Al-Rubaie Jerome Chang 49 335 0 27 Mar 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 76 467 0 31 Jan 2018
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models Wieland Brendel Jonas Rauber Matthias Bethge AAML 65 1,342 0 12 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 263 12,029 0 19 Jun 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 118 1,814 0 16 Jun 2017
Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN Weiwei Hu Ying Tan GAN 65 461 0 20 Feb 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 220 8,533 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 517 5,885 0 08 Jul 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 74 3,955 0 24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 115 4,886 0 14 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 58 3,066 0 14 Nov 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 302 19,580 0 09 Mar 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 225 19,017 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 233 14,893 1 21 Dec 2013