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Towards Security Threats of Deep Learning Systems: A Survey

28 November 2019

Papers citing "Towards Security Threats of Deep Learning Systems: A Survey"

46 / 46 papers shown

Title
Support Vector Machines under Adversarial Label Contamination Huang Xiao Battista Biggio B. Nelson Han Xiao Claudia Eckert Fabio Roli AAML 56 231 0 01 Jun 2022
Is Data Clustering in Adversarial Settings Secure? Battista Biggio I. Pillai Samuel Rota Buló Andrea Valenza Marcello Pelillo Fabio Roli AAML 48 130 0 25 Nov 2018
Data Poisoning Attacks against Online Learning Yizhen Wang Kamalika Chaudhuri AAML 62 93 0 27 Aug 2018
Security and Privacy Issues in Deep Learning Ho Bae Jaehee Jang Dahuin Jung Hyemi Jang Heonseok Ha Hyungyu Lee Sungroh Yoon SILM MIACV 118 78 0 31 Jul 2018
Efficient Deep Learning on Multi-Source Private Data Nicholas Hynes Raymond Cheng Basel Alomair FedML 62 102 0 17 Jul 2018
Machine Learning with Membership Privacy using Adversarial Regularization Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV 52 472 0 16 Jul 2018
Algorithms that Remember: Model Inversion Attacks and Data Protection Law Michael Veale Reuben Binns L. Edwards 46 197 0 12 Jul 2018
Privacy-preserving Machine Learning through Data Obfuscation Tianwei Zhang Zecheng He R. Lee 67 80 0 05 Jul 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 85 761 0 01 Apr 2018
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems Lei Ma Felix Juefei Xu Fuyuan Zhang Jiyuan Sun Minhui Xue ... Ting Su Li Li Yang Liu Jianjun Zhao Yadong Wang ELM 67 622 0 20 Mar 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 130 138 0 27 Feb 2018
Stealing Hyperparameters in Machine Learning Binghui Wang Neil Zhenqiang Gong AAML 144 466 0 14 Feb 2018
CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition Xuejing Yuan Yuxuan Chen Yue Zhao Yunhui Long Xiaokang Liu Kai Chen Shengzhi Zhang Heqing Huang Xiaofeng Wang Carl A. Gunter AAML 66 354 0 24 Jan 2018
Gazelle: A Low Latency Framework for Secure Neural Network Inference Chiraag Juvekar Vinod Vaikuntanathan A. Chandrakasan 65 893 0 16 Jan 2018
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers Ji Gao Jack Lanchantin M. Soffa Yanjun Qi AAML 137 721 0 13 Jan 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text Nicholas Carlini D. Wagner AAML 97 1,083 0 05 Jan 2018
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 152 682 0 26 Nov 2017
Mitigating Adversarial Effects Through Randomization Cihang Xie Jianyu Wang Zhishuai Zhang Zhou Ren Alan Yuille AAML 113 1,059 0 06 Nov 2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen Yash Sharma Huan Zhang Jinfeng Yi Cho-Jui Hsieh AAML 66 641 0 13 Sep 2017
Towards Proving the Adversarial Robustness of Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel J. Kochenderfer AAML OOD 80 118 0 08 Sep 2017
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization Luis Muñoz-González Battista Biggio Ambra Demontis Andrea Paudice Vasin Wongrassamee Emil C. Lupu Fabio Roli AAML 99 633 0 29 Aug 2017
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars Yuchi Tian Kexin Pei Suman Jana Baishakhi Ray AAML 64 1,359 0 28 Aug 2017
Efficient Defenses Against Adversarial Attacks Valentina Zantedeschi Maria-Irina Nicolae Ambrish Rawat AAML 46 297 0 21 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 310 12,069 0 19 Jun 2017
Certified Defenses for Data Poisoning Attacks Jacob Steinhardt Pang Wei Koh Percy Liang AAML 105 755 0 09 Jun 2017
Towards Robust Detection of Adversarial Examples Tianyu Pang Chao Du Yinpeng Dong Jun Zhu AAML 69 18 0 02 Jun 2017
Black-Box Attacks against RNN based Malware Detection Algorithms Weiwei Hu Ying Tan 44 150 0 23 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,725 0 19 May 2017
The Space of Transferable Adversarial Examples Florian Tramèr Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML SILM 90 557 0 11 Apr 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 120 1,404 0 24 Feb 2017
Adversarial examples for generative models Jernej Kos Ian S. Fischer Basel Alomair GAN 72 274 0 22 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 472 3,144 0 04 Nov 2016
Universal adversarial perturbations Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi Omar Fawzi P. Frossard AAML 145 2,527 0 26 Oct 2016
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 261 4,135 0 18 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 107 1,807 0 09 Sep 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 266 8,555 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 543 5,897 0 08 Jul 2016
Bag of Tricks for Efficient Text Classification Armand Joulin Edouard Grave Piotr Bojanowski Tomas Mikolov VLM 175 4,622 0 06 Jul 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,130 0 01 Jul 2016
Crafting Adversarial Input Sequences for Recurrent Neural Networks Nicolas Papernot Patrick McDaniel A. Swami Richard E. Harang AAML GAN SILM 51 456 0 28 Apr 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,678 0 08 Feb 2016
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 151 4,897 0 14 Nov 2015
Learning with a Strong Adversary Ruitong Huang Bing Xu Dale Schuurmans Csaba Szepesvári AAML 79 358 0 10 Nov 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 277 14,927 1 21 Dec 2013
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers G. Ateniese G. Felici L. Mancini A. Spognardi Antonio Villani Domenico Vitali 84 462 0 19 Jun 2013
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 115 1,593 0 27 Jun 2012