Security Analysis and Enhancement of Model Compressed Deep Learning
Systems under Adversarial Attacks

Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks

14 February 2018

Qi Liu

Papers citing "Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks"

8 / 8 papers shown

Title
Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation Cheems Wang Yiqin Lv Yixiu Mao Yun Qu Yi Tian Xu Xiangyang Ji OOD TTA 82 7 0 28 Jul 2024
RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks Alberto Marchisio Vojtěch Mrázek Andrea Massa Beatrice Bussolino Maurizio Martina Mohamed Bennai AAML 46 5 0 11 Oct 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 212 345 0 15 Dec 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 43 17 0 09 Nov 2021
Blockchain and AI-based Solutions to Combat Coronavirus (COVID-19)-like Epidemics: A Survey Dinh C. Nguyen Ming Ding P. Pathirana Aruna Seneviratne 30 179 0 28 Jun 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack Mengting Xu Tao Zhang Zhongnian Li Mingxia Liu Daoqiang Zhang AAML OOD MedIm 33 41 0 05 Mar 2021
Interpreting and Evaluating Neural Network Robustness Fuxun Yu Zhuwei Qin Chenchen Liu Liang Zhao Yanzhi Wang Xiang Chen AAML 15 55 0 10 May 2019
POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm Jinyin Chen Mengmeng Su Shijing Shen Hui Xiong Haibin Zheng AAML 22 67 0 01 May 2019