Results 81 to 90 of about 177,286 (215)

A survey of practical adversarial example attacks

Cybersecurity, 2018
Adversarial examples revealed the weakness of machine learning techniques in terms of robustness, which moreover inspired adversaries to make use of the weakness to attack systems employing machine learning.
Lu Sun, Mingtian Tan, Zhe Zhou
doaj   +1 more source

Frequency-Guided Word Substitutions for Detecting Textual Adversarial\n Examples [PDF]

, 2020
Maximilian Mozes, Pontus Stenetorp, Bennett Kleinberg, Lewis D. Griffin   +3 more
openalex   +1 more source

DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection [PDF]

, 2023
Jiang Liu, Chun Pong Lau, Guo, Zhongliang, Guo, Yuxiang, Wang, Zhaoyang, Chellappa, Rama   +5 more
openalex   +1 more source

Invisible Perturbations: Physical Adversarial Examples Exploiting the\n Rolling Shutter Effect [PDF]

, 2020
Athena Sayles, Ashish Hooda, Mohit Gupta, Rahul Chatterjee, Earlence Fernandes   +4 more
openalex   +1 more source

Transferable Adversarial Examples with Bayes Approach [PDF]

, 2022
Mingyuan Fan, Cen Chen, Zhou, Wenmeng, Wang, Yinggui   +3 more
openalex   +1 more source

Weighted Average Precision: Adversarial Example Detection in the Visual Perception of Autonomous Vehicles [PDF]

, 2020
Yilan Li, Senem Velipasalar
openalex   +1 more source

On the Veracity of Local, Model-agnostic Explanations in Audio\n Classification: Targeted Investigations with Adversarial Examples [PDF]

, 2021
Verena Praher, Katharina Prinz, Arthur Flexer, Gerhard Widmer   +3 more
openalex   +1 more source

Provably Robust Adversarial Examples

, 2020
International Conference on Learning Representations (ICLR 2022)
Dimitar Iliev Dimitrov, Gagandeep Singh 0001, Timon Gehr, Martin T. Vechev   +3 more
openaire   +4 more sources

Cross-Gen: An Efficient Generator Network for Adversarial Attacks on Cross-Modal Hashing Retrieval

Future Internet
Research on deep neural network (DNN)-based multi-dimensional data visualization has thoroughly explored cross-modal hash retrieval (CMHR) systems, yet their vulnerability to malicious adversarial examples remains evident.
Chao Hu, Li Chen, Sisheng Li, Yin Yi, Yu Zhan, Chengguang Liu, Jianling Liu, Ronghua Shi   +7 more
doaj   +1 more source

Adversarial Examples for CNN-Based Malware Detectors

IEEE Access, 2019
The convolutional neural network (CNN)-based models have achieved tremendous breakthroughs in many end-to-end applications, such as image identification, text classification, and speech recognition.
Bingcai Chen, Zhongru Ren, Chao Yu, Iftikhar Hussain, Jintao Liu   +4 more
doaj   +1 more source