Adversarial Examples: Attacks and Defenses for Deep Learning

19 December 2017

Papers citing "Adversarial Examples: Attacks and Defenses for Deep Learning"

50 / 234 papers shown

Title
Incorrect by Construction: Fine Tuning Neural Networks for Guaranteed Performance on Finite Sets of Examples I. Papusha Rosa Wu Joshua Brulé Yanni Kouskoulas D. Genin Aurora C. Schmidt 13 5 0 03 Aug 2020
On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations Md Rafiqul Islam Rabin Nghi D. Q. Bui Ke Wang Yijun Yu Lingxiao Jiang Mohammad Amin Alipour 30 90 0 31 Jul 2020
Cassandra: Detecting Trojaned Networks from Adversarial Perturbations Xiaoyu Zhang Ajmal Mian Rohit Gupta Nazanin Rahnavard M. Shah AAML 30 26 0 28 Jul 2020
Diagnosing Concept Drift with Visual Analytics Weikai Yang Zhuguo Li Mengchen Liu Yafeng Lu Kelei Cao Ross Maciejewski Shixia Liu 47 33 0 28 Jul 2020
Backdoor Learning: A Survey Yiming Li Yong Jiang Zhifeng Li Shutao Xia AAML 45 589 0 17 Jul 2020
Adversarial jamming attacks and defense strategies via adaptive deep reinforcement learning Feng Wang Chen Zhong M. C. Gursoy Senem Velipasalar AAML 18 8 0 12 Jul 2020
Differentiable Language Model Adversarial Attacks on Categorical Sequence Classifiers I. Fursov A. Zaytsev Nikita Klyuchnikov A. Kravchenko E. Burnaev AAML SILM 29 5 0 19 Jun 2020
Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples Kaleel Mahmood Deniz Gurevin Marten van Dijk Phuong Ha Nguyen AAML 22 22 0 18 Jun 2020
Defensive Approximation: Securing CNNs using Approximate Computing Amira Guesmi Ihsen Alouani Khaled N. Khasawneh M. Baklouti T. Frikha Mohamed Abid Nael B. Abu-Ghazaleh AAML 19 37 0 13 Jun 2020
Scalable Partial Explainability in Neural Networks via Flexible Activation Functions S. Sun Chen Li Zhuangkun Wei Antonios Tsourdos Weisi Guo FAtt 32 2 0 10 Jun 2020
DeepSonar: Towards Effective and Robust Detection of AI-Synthesized Fake Voices Run Wang Felix Juefei Xu Yihao Huang Qing Guo Xiaofei Xie Lei Ma Yang Liu AAML 25 105 0 28 May 2020
Chat as Expected: Learning to Manipulate Black-box Neural Dialogue Models Haochen Liu Zhiwei Wang Tyler Derr Jiliang Tang AAML 22 15 0 27 May 2020
Vulnerability of deep neural networks for detecting COVID-19 cases from chest X-ray images to universal adversarial attacks Hokuto Hirano K. Koga Kazuhiro Takemoto AAML 24 47 0 22 May 2020
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images Yixing Huang Alexander Preuhs M. Manhart G. Lauritsch Andreas Maier MedIm 27 5 0 20 May 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 30 29 0 17 May 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 19 91 0 05 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 41 371 0 30 Apr 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning Xinjian Luo Xiangqi Zhu FedML 73 25 0 27 Apr 2020
The Attacker's Perspective on Automatic Speaker Verification: An Overview Rohan Kumar Das Xiaohai Tian Tomi Kinnunen Haizhou Li AAML 20 81 0 19 Apr 2020
Dynamic Knowledge Graph-based Dialogue Generation with Improved Adversarial Meta-Learning Hongcai Xu J. Bao Gaojie Zhang 22 8 0 19 Apr 2020
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning Michael Everett Bjorn Lutjens Jonathan P. How AAML 13 41 0 11 Apr 2020
Editable Neural Networks A. Sinitsin Vsevolod Plokhotnyuk Dmitriy V. Pyrkin Sergei Popov Artem Babenko KELM 68 175 0 01 Apr 2020
When the Guard failed the Droid: A case study of Android malware Harel Berger Chen Hajaj A. Dvir AAML 30 7 0 31 Mar 2020
Quantum noise protects quantum classifiers against adversaries Yuxuan Du Min-hsiu Hsieh Tongliang Liu Dacheng Tao Nana Liu AAML 22 110 0 20 Mar 2020
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions Zebin Yang Aijun Zhang Agus Sudjianto FAtt 19 126 0 16 Mar 2020
ConAML: Constrained Adversarial Machine Learning for Cyber-Physical Systems Jiangnan Li Yingyuan Yang Jinyuan Stella Sun K. Tomsovic Jin Young Lee AAML 28 52 0 12 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 67 63 0 02 Mar 2020
Adversarial Ranking Attack and Defense Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 36 38 0 26 Feb 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 27 0 0 25 Feb 2020
Real-Time Detectors for Digital and Physical Adversarial Inputs to Perception Systems Y. Kantaros Taylor J. Carpenter Kaustubh Sridhar Yahan Yang Insup Lee James Weimer AAML 17 12 0 23 Feb 2020
AI safety: state of the field through quantitative lens Mislav Juric A. Sandic Mario Brčič 25 24 0 12 Feb 2020
On the Robustness of Face Recognition Algorithms Against Attacks and Bias Richa Singh Akshay Agarwal Maneet Singh Shruti Nagpal Mayank Vatsa CVBM AAML 49 65 0 07 Feb 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks Oliver Willers Sebastian Sudholt Shervin Raafatnia Stephanie Abrecht 28 80 0 22 Jan 2020
Deep Learning-Based Solvability of Underdetermined Inverse Problems in Medical Imaging Chang Min Hyun Seong Hyeon Baek M. Lee S. Lee J.K. Seo 27 39 0 06 Jan 2020
A Survey of Deep Learning Applications to Autonomous Vehicle Control Sampo Kuutti Richard Bowden Yaochu Jin P. Barber Saber Fallah 36 506 0 23 Dec 2019
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing Bernhard Stimpel Christopher Syben Franziska Schirrmacher P. Hoelter Arnd Dörfler Andreas Maier MedIm 24 23 0 18 Nov 2019
Simple iterative method for generating targeted universal adversarial perturbations Hokuto Hirano Kazuhiro Takemoto AAML 27 30 0 15 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 18 104 0 13 Nov 2019
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 37 68 0 06 Nov 2019
Effectiveness of random deep feature selection for securing image manipulation detectors against adversarial examples Mauro Barni Ehsan Nowroozi B. Tondi Bowen Zhang AAML 11 17 0 25 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 39 6,119 0 22 Oct 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 20 1 0 19 Sep 2019
Say What I Want: Towards the Dark Side of Neural Dialogue Models Haochen Liu Tyler Derr Zitao Liu Jiliang Tang 31 16 0 13 Sep 2019
Detection of Backdoors in Trained Classifiers Without Access to the Training Set Zhen Xiang David J. Miller G. Kesidis AAML 22 23 0 27 Aug 2019
Defending Against Adversarial Iris Examples Using Wavelet Decomposition Sobhan Soleymani Ali Dabouei J. Dawson Nasser M. Nasrabadi AAML 27 9 0 08 Aug 2019
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference Yonatan Belinkov Adam Poliak Stuart M. Shieber Benjamin Van Durme Alexander M. Rush 27 94 0 09 Jul 2019
Generative Counterfactual Introspection for Explainable Deep Learning Shusen Liu B. Kailkhura Donald Loveland Yong Han 25 90 0 06 Jul 2019
A Game-Theoretic Approach to Adversarial Linear Support Vector Classification Farhad Farokhi AAML 27 3 0 24 Jun 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 21 187 0 29 May 2019
A framework for the extraction of Deep Neural Networks by leveraging public data Soham Pal Yash Gupta Aditya Shukla Aditya Kanade S. Shevade V. Ganapathy FedML MLAU MIACV 36 56 0 22 May 2019