Adversarial Examples: Opportunities and Challenges

13 September 2018

Papers citing "Adversarial Examples: Opportunities and Challenges"

27 / 27 papers shown

Title
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 33 2 0 09 Oct 2024
FedAT: Federated Adversarial Training for Distributed Insider Threat Detection R. Gayathri Atul Sajjanhar Md Palash Uddin Yong Xiang FedML 23 0 0 19 Sep 2024
CPSDBench: A Large Language Model Evaluation Benchmark and Baseline for Chinese Public Security Domain Xin Tong Bo Jin Zhi Lin Binjun Wang Ting Yu Qiang Cheng ELM 25 0 0 11 Feb 2024
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems Guangjing Wang Ce Zhou Yuanda Wang Bocheng Chen Hanqing Guo Qiben Yan AAML SILM 68 3 0 20 Nov 2023
Madvex: Instrumentation-based Adversarial Attacks on Machine Learning Malware Detection Yang Cai Felix Mächtle C. Daskalakis Volodymyr Bezsmertnyi T. Eisenbarth AAML 31 7 0 04 May 2023
Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective Baoyuan Wu Zihao Zhu Li Liu Qingshan Liu Zhaofeng He Siwei Lyu AAML 44 21 0 19 Feb 2023
Imperceptible Sample-Specific Backdoor to DNN with Denoising Autoencoder Jiliang Zhang Jing Xu Zhi-Li Zhang Yansong Gao AAML 27 2 0 09 Feb 2023
Deep Fake Detection, Deterrence and Response: Challenges and Opportunities Amin Azmoodeh Ali Dehghantanha 45 2 0 26 Nov 2022
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey Huiyun Cao Wenlong Zou Yinkun Wang Ting Song Mengjun Liu AAML 54 5 0 19 Oct 2022
Resisting Deep Learning Models Against Adversarial Attack Transferability via Feature Randomization Ehsan Nowroozi Mohammadreza Mohammadi Pargol Golmohammadi Yassine Mekdad Mauro Conti Selcuk Uluagac AAML SILM 38 13 0 11 Sep 2022
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems Wei Jia Zhaojun Lu Haichun Zhang Zhenglin Liu Jie Wang Gang Qu AAML 16 51 0 17 Jan 2022
On the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Driving Giulio Rossolini F. Nesti G. D’Amico Saasha Nair Alessandro Biondi Giorgio Buttazzo AAML 33 37 0 05 Jan 2022
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art Xiang Ling Lingfei Wu Jiangyu Zhang Zhenqing Qu Wei Deng ... Chunming Wu S. Ji Tianyue Luo Jingzheng Wu Yanjun Wu AAML 44 74 0 23 Dec 2021
Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities Indranil Pan L. Mason Omar K. Matar AI4CE 44 45 0 07 Nov 2021
Demystifying the Transferability of Adversarial Attacks in Computer Networks Ehsan Nowroozi Yassine Mekdad Mohammad Hajian Berenjestanaki Mauro Conti Abdeslam El Fergougui AAML 42 32 0 09 Oct 2021
STARdom: an architecture for trusted and secure human-centered manufacturing systems Jože M. Rožanec Patrik Zajec K. Kenda I. Novalija B. Fortuna ... Diego Reforgiato Recupero D. Kyriazis G. Sofianidis Spyros Theodoropoulos John Soldatos 31 7 0 02 Apr 2021
Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting F. Nesti Alessandro Biondi Giorgio Buttazzo AAML 15 39 0 27 Jan 2021
Robustness of on-device Models: Adversarial Attack to Deep Learning Models on Android Apps Yujin Huang Han Hu Chunyang Chen AAML FedML 74 33 0 12 Jan 2021
ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries Jinyin Chen Zhen Wang Haibin Zheng Jun Xiao Zhaoyan Ming AAML 19 5 0 18 Dec 2020
Towards Robust Neural Networks via Orthogonal Diversity Kun Fang Qinghua Tao Yingwen Wu Tao Li Jia Cai Feipeng Cai Xiaolin Huang Jie-jin Yang AAML 41 8 0 23 Oct 2020
Boosting Gradient for White-Box Adversarial Attacks Hongying Liu Zhenyu Zhou Fanhua Shang Xiaoyu Qi Yuanyuan Liu L. Jiao AAML 24 7 0 21 Oct 2020
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review Yansong Gao Bao Gia Doan Zhi-Li Zhang Siqi Ma Jiliang Zhang Anmin Fu Surya Nepal Hyoungshick Kim AAML 36 220 0 21 Jul 2020
AI safety: state of the field through quantitative lens Mislav Juric A. Sandic Mario Brčič 25 24 0 12 Feb 2020
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks Yizhen Dong Peixin Zhang Jingyi Wang Shuang Liu Jun Sun Jianye Hao Xinyu Wang Li Wang J. Dong Ting Dai OOD AAML 21 32 0 14 Nov 2019
Adversarial Robustness via Label-Smoothing Morgane Goibert Elvis Dohmatob AAML 10 18 0 27 Jun 2019
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,113 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 308 5,847 0 08 Jul 2016