Results 21 to 30 of about 6,306,959 (200)

Adversarial Machine Learning [PDF]

IEEE Internet Computing, 2011
The author briefly introduces the emerging field of adversarial machine learning, in which opponents can cause traditional machine learning algorithms to behave poorly in security applications. He gives a high-level overview and mentions several types of attacks, as well as several types of defenses, and theoretical limits derived from a study of near ...
Ling Huang 0001, Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, J. D. Tygar   +4 more
openaire   +3 more sources

Adversarial-Aware Deep Learning System Based on a Secondary Classical Machine Learning Verification Approach

Sensors, 2023
Deep learning models have been used in creating various effective image classification applications. However, they are vulnerable to adversarial attacks that seek to misguide the models into predicting incorrect classes.
Mohammed Alkhowaiter, Hisham Kholidy, Mnassar A. Alyami, Abdulmajeed Alghamdi, Cliff Zou   +4 more
doaj   +1 more source

Adversarial Malware Generation Method Based on Genetic Algorithm [PDF]

Jisuanji kexue, 2023
In recent years,with the development of Internet technology,malware has become an important method of network attack.To defend against malware attacks,deep learning techniques can be applied to malware detection.However,due to the limitations of deep ...
LI Kun, GUO Wei, ZHANG Fan, DU Jiayu, YANG Meiyue
doaj   +1 more source

Targeted Universal Adversarial Examples for Remote Sensing

Remote Sensing, 2022
Researchers are focusing on the vulnerabilities of deep learning models for remote sensing; various attack methods have been proposed, including universal adversarial examples.
Tao Bai, Hao Wang, Bihan Wen
doaj   +1 more source

Adversarial Examples Detection Method Based on Image Denoising and Compression [PDF]

Jisuanji gongcheng, 2023
Numerous deep learning achievements in the field of computer vision have been widely applied in real life. However, adversarial examples can lead to false positives in deep learning models with high confidence, resulting in serious security consequences.
Feiyu WANG, Fan ZHANG, Jiayu DU, Hongle LEI, Xiaofeng QI
doaj   +1 more source

Learning to Characterize Adversarial Subspaces [PDF]

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Submitted to ICASSP ...
Xiaofeng Mao, Yuefeng Chen, Yuhong Li, Yuan He 0011, Hui Xue 0001   +4 more
openaire   +3 more sources

Deep Adversarial Reinforcement Learning Method to Generate Control Policies Robust Against Worst-Case Value Predictions

IEEE Access, 2023
Over the last decade, methods for autonomous control by artificial intelligence have been extensively developed based on deep reinforcement learning (DRL) technologies.
Kohei Ohashi, Kosuke Nakanishi, Yuji Yasui, Shin Ishii   +3 more
doaj   +1 more source

Adversarial Robustness of Deep Reinforcement Learning Based Dynamic Recommender Systems

Frontiers in Big Data, 2022
Adversarial attacks, e.g., adversarial perturbations of the input and adversarial samples, pose significant challenges to machine learning and deep learning techniques, including interactive recommendation systems.
Siyu Wang, Yuanjiang Cao, Xiaocong Chen, Lina Yao, Xianzhi Wang, Quan Z. Sheng   +5 more
doaj   +1 more source

Adversarial Learning for Product Recommendation [PDF]

AI, 2020
Product recommendation can be considered as a problem in data fusion—estimation of the joint distribution between individuals, their behaviors, and goods or services of interest. This work proposes a conditional, coupled generative adversarial network (RecommenderGAN) that learns to produce samples from a joint distribution between (view, buy ...
Joel R. Bock, Akhilesh Maewal
openaire   +2 more sources

A Brute-Force Black-Box Method to Attack Machine Learning-Based Systems in Cybersecurity

IEEE Access, 2020
Machine learning algorithms are widely utilized in cybersecurity. However, recent studies show that machine learning algorithms are vulnerable to adversarial examples.
Sicong Zhang, Xiaoyao Xie, Yang Xu
doaj   +1 more source