Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

24 May 2016

Papers citing "Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples"

50 / 360 papers shown

Title
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples Deqiang Li Ramesh Baral Tao Li Han Wang Qianmu Li Shouhuai Xu AAML 28 21 0 18 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku Issei Sato AAML 24 62 0 11 Sep 2018
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks Ambra Demontis Marco Melis Maura Pintor Matthew Jagielski Battista Biggio Alina Oprea Cristina Nita-Rotaru Fabio Roli SILM AAML 19 11 0 08 Sep 2018
Adversarial Reprogramming of Text Classification Neural Networks Paarth Neekhara Shehzeen Samarah Hussain Shlomo Dubnov F. Koushanfar AAML SILM 29 9 0 06 Sep 2018
Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding Lea Schonherr Katharina Kohls Steffen Zeiler Thorsten Holz D. Kolossa AAML 33 287 0 16 Aug 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D. Su Huan Zhang Hongge Chen Jinfeng Yi Pin-Yu Chen Yupeng Gao VLM 40 389 0 05 Aug 2018
Enabling Trust in Deep Learning Models: A Digital Forensics Case Study Aditya K Slawomir Grzonkowski NhienAn Lekhac 19 27 0 03 Aug 2018
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service L. Hanzlik Yang Zhang Kathrin Grosse A. Salem Maximilian Augustin Michael Backes Mario Fritz OffRL 22 103 0 01 Aug 2018
Harmonic Adversarial Attack Method Wen Heng Shuchang Zhou Tingting Jiang AAML 22 6 0 18 Jul 2018
Adversarial Examples in Deep Learning: Characterization and Divergence Wenqi Wei Ling Liu Margaret Loper Stacey Truex Lei Yu Mehmet Emre Gursoy Yanzhao Wu AAML SILM 33 18 0 29 Jun 2018
Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data Jacson Rodrigues Correia-Silva Rodrigo Berriel C. Badue Alberto F. de Souza Thiago Oliveira-Santos MLAU 14 174 0 14 Jun 2018
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders Partha Ghosh Arpan Losalka Michael J. Black AAML 21 77 0 31 May 2018
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks Chun-Chen Tu Pai-Shun Ting Pin-Yu Chen Sijia Liu Huan Zhang Jinfeng Yi Cho-Jui Hsieh Shin-Ming Cheng MLAU AAML 26 395 0 30 May 2018
Laplacian Networks: Bounding Indicator Function Smoothness for Neural Network Robustness Carlos Lassance Vincent Gripon Antonio Ortega AAML 24 16 0 24 May 2018
Towards Robust Training of Neural Networks by Regularizing Adversarial Gradients Fuxun Yu Zirui Xu Yanzhi Wang Chenchen Liu Xiang Chen AAML 18 10 0 23 May 2018
Adversarially Robust Training through Structured Gradient Regularization Kevin Roth Aurelien Lucchi Sebastian Nowozin Thomas Hofmann 30 23 0 22 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 21 41 0 14 May 2018
Black-box Adversarial Attacks with Limited Queries and Information Andrew Ilyas Logan Engstrom Anish Athalye Jessy Lin MLAU AAML 70 1,191 0 23 Apr 2018
Adversarial Attacks Against Medical Deep Learning Systems S. G. Finlayson Hyung Won Chung I. Kohane Andrew L. Beam SILM AAML OOD MedIm 25 230 0 15 Apr 2018
Bypassing Feature Squeezing by Increasing Adversary Strength Yash Sharma Pin-Yu Chen AAML 19 34 0 27 Mar 2018
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 17 26 0 26 Mar 2018
Clipping free attacks against artificial neural networks B. Addad Jérôme Kodjabachian Christophe Meyer AAML 16 1 0 26 Mar 2018
Security Theater: On the Vulnerability of Classifiers to Exploratory Attacks Tegjyot Singh Sethi M. Kantardzic J. Ryu AAML 23 11 0 24 Mar 2018
A Dynamic-Adversarial Mining Approach to the Security of Machine Learning Tegjyot Singh Sethi M. Kantardzic Lingyu Lyu Jiashun Chen AAML 16 11 0 24 Mar 2018
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 40 286 0 19 Mar 2018
Understanding and Enhancing the Transferability of Adversarial Examples Lei Wu Zhanxing Zhu Cheng Tai E. Weinan AAML SILM 30 97 0 27 Feb 2018
Are Generative Classifiers More Robust to Adversarial Attacks? Yingzhen Li John Bradshaw Yash Sharma AAML 57 78 0 19 Feb 2018
DARTS: Deceiving Autonomous Cars with Toxic Signs Chawin Sitawarin A. Bhagoji Arsalan Mosenia M. Chiang Prateek Mittal AAML 37 233 0 18 Feb 2018
Few-shot learning of neural networks from scratch by pseudo example optimization Akisato Kimura Zoubin Ghahramani Koh Takeuchi Tomoharu Iwata N. Ueda 35 52 0 08 Feb 2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality Xingjun Ma Bo-wen Li Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck D. Song Michael E. Houle James Bailey AAML 43 730 0 08 Jan 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text Nicholas Carlini D. Wagner AAML 38 1,074 0 05 Jan 2018
Query-limited Black-box Attacks to Classifiers Fnu Suya Yuan Tian David Evans Paolo Papotti AAML 20 24 0 23 Dec 2017
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Bo-wen Li Kimberly Lu D. Song AAML SILM 44 1,808 0 15 Dec 2017
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 31 351 0 06 Dec 2017
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning Hongge Chen Huan Zhang Pin-Yu Chen Jinfeng Yi Cho-Jui Hsieh GAN AAML 35 49 0 06 Dec 2017
Hardening Quantum Machine Learning Against Adversaries N. Wiebe Ramnath Kumar AAML 25 20 0 17 Nov 2017
Towards Reverse-Engineering Black-Box Neural Networks Seong Joon Oh Maximilian Augustin Bernt Schiele Mario Fritz AAML 292 3 0 06 Nov 2017
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 40 596 0 31 Oct 2017
Neural Trojans Yuntao Liu Yang Xie Ankur Srivastava AAML 13 350 0 03 Oct 2017
PassGAN: A Deep Learning Approach for Password Guessing Briland Hitaj Paolo Gasti G. Ateniese Fernando Perez-Cruz GAN 30 246 0 01 Sep 2017
Towards Crafting Text Adversarial Samples Suranjana Samanta S. Mehta AAML 27 219 0 10 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks A. Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 89 11,872 0 19 Jun 2017
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong Warren He James Wei Xinyun Chen Nicholas Carlini D. Song AAML 43 242 0 15 Jun 2017
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples Yizhen Wang S. Jha Kamalika Chaudhuri AAML 19 154 0 13 Jun 2017
Towards Robust Detection of Adversarial Examples Tianyu Pang Chao Du Yinpeng Dong Jun Zhu AAML 39 18 0 02 Jun 2017
Black-Box Attacks against RNN based Malware Detection Algorithms Weiwei Hu Ying Tan 10 149 0 23 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 61 1,842 0 20 May 2017
The Space of Transferable Adversarial Examples Florian Tramèr Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML SILM 41 555 0 11 Apr 2017
Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective Seong Joon Oh Mario Fritz Bernt Schiele CVBM AAML 339 160 0 28 Mar 2017
Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains Tegjyot Singh Sethi M. Kantardzic AAML 27 49 0 23 Mar 2017