Results 51 to 60 of about 5,380,268 (331)
BAE: BERT-based Adversarial Examples for Text Classification [PDF]
Conference on Empirical Methods in Natural Language Processing, 2020 Modern text classification models are susceptible to adversarial examples, perturbed versions of the original text indiscernible by humans but which get misclassified by the model.
Siddhant Garg, Goutham Ramakrishnan
semanticscholar +1 more source
Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples [PDF]
Neural Information Processing Systems, 2023 Backdoor attacks are serious security threats to machine learning models where an adversary can inject poisoned samples into the training set, causing a backdoored model which predicts poisoned samples with particular triggers to particular target ...
Shaokui Wei +3 more
semanticscholar +1 more source
Adversarial Examples for Good: Adversarial Examples Guided Imbalanced Learning
2022 IEEE International Conference on Image Processing (ICIP), 2022 Appeared in ICIP ...
Jie Zhang 0081 +3 more
openaire +2 more sources
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text [PDF]
2018 IEEE Security and Privacy Workshops (SPW), 2018 We construct targeted audio adversarial examples on automatic speech recognition. Given any audio waveform, we can produce another that is over 99.9% similar, but transcribes as any phrase we choose (recognizing up to 50 characters per second of audio ...
Nicholas Carlini, D. Wagner
semanticscholar +1 more source
IEEE Access, 2020 Deep neural networks (DNNs) have achieved great success in various applications due to their strong expressive power. However, recent studies have shown that DNNs are vulnerable to adversarial examples, and these manipulated instances can mislead DNN ...
Jianyi Liu +4 more
doaj +1 more source
Exploiting Doubly Adversarial Examples for Improving Adversarial Robustness
, 2022 Deep neural networks have shown outstanding performance in various areas, but adversarial examples can easily fool them. Although strong adversarial attacks have defeated diverse adversarial defense methods, adversarial training, which augments training ...
Cho, Seungju +3 more
core +1 more source
Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT
, 2021 As the internet continues to be populated with new devices and emerging technologies, the attack surface grows exponentially. Technology is shifting towards a profit-driven Internet of Things market where security is an afterthought.
William J. Buchanan +13 more
core +1 more source
Recovery of Adversarial Examples Based on SmsGAN [PDF]
Zhengzhou Daxue xuebao. Gongxue ban, 2021 Due to adversarial examples′ serious interference to the detection models based on deep learning, a recovery method of adversarial examples based on stochastic multihlter statistical generative adversarial network (SmsGAN) was proposed in this work.
ZHAO Junjie, WANG Jinwei
doaj +1 more source
Adversarial Examples for Evaluating Reading Comprehension Systems [PDF]
Conference on Empirical Methods in Natural Language Processing, 2017 Standard accuracy metrics indicate that reading comprehension systems are making rapid progress, but the extent to which these systems truly understand language remains unclear.
Robin Jia, Percy Liang
semanticscholar +1 more source
Misusing Tools in Large Language Models With Visual Adversarial Examples [PDF]
arXiv.org, 2023 Large Language Models (LLMs) are being enhanced with the ability to use tools and to process multiple modalities. These new capabilities bring new benefits and also new security risks.
Xiaohan Fu +6 more
semanticscholar +1 more source