Results 91 to 100 of about 12,832 (282)

The model of network adversarial attack.

, 2022
(a) The structure of DCNN for experiment. (b) The model of network adversarial attack.
Zeyu Yu (9472333), Yanrong Cui (12506170), Hongqiang Yuan (12506167), Dingming Yang (8505990)   +3 more
core   +1 more source

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

Energy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom, Lotfi Saidi, Eric Bechhoefer   +2 more
wiley   +1 more source

DeeBBAA: A Benchmark Deep Black Box Adversarial Attack Against Cyber-Physical Power Systems

Cyber-physical infrastructure faces threats from evasive false data injection attacks that can significantly impact their security and performance. Adversarial attacks are a popular evasive false data injection threat model that generally targets AI/ML ...
Tushar, W, Saha, TK, Bhattacharjee, A, Mishra, S, Verma, A, Bai, G   +5 more
core   +1 more source

A Comprehensive Review of AI‐Powered Energy Systems

Energy Science &Engineering, EarlyView.
The role of Artificial Intelligence (AI) in developing next‐generation energy systems is getting more day by day. Therefore, incorporating AI enables real‐time decision‐making and advanced grid management, which are essential for optimizing the use of intermittent renewable sources like wind and solar power.
Armin Razmjoo, Pedram Asef, Masoumeh Javadi, Mousa Marzband, Shady S. Refaat, Muhyaddin Rawa   +5 more
wiley   +1 more source

Benign-salient Region Based End-to-End Adversarial Malware Generation Method [PDF]

Jisuanji kexue
Malware detection methods combining visualization techniques and deep learning have gained widespread attention due to their high accuracy and low cost.However,deep learning models are vulnerable to adversarial attacks,where intentional small-scale ...
YUAN Mengjiao, LU Tianliang, HUANG Wanxin, HE Houhan
doaj   +1 more source

Benign Adversarial Attack: Tricking Models for Goodness

, 2022
In spite of the successful application in many fields, machine learning models today suffer from notorious problems like vulnerability to adversarial examples.
Lin, Zhiyu, Sang, Jitao, Zhang, Jiaming, Zhao, Xian   +3 more
core   +1 more source

Spatial omics in the AI era: Technologies, algorithmic ecosystems, biological applications, and large model perspectives

iMeta, EarlyView.
This review focuses on spatial omics, covering the introduction and comparison of technology platforms, explanation and recommendation of algorithm ecology, demonstration of biological applications, and prospect of large models. It aims to help researchers in the interdisciplinary field of spatial omics quickly understand the current situation and ...
Haoxiu Wang, Xinwang Yang, Siheng Wang, Zhe Yang, Xiuhui Yang, Yutong Yang, Zirong Li, Yuqi Ren, Qianqian Zhang, Bowen Zhao, Jingming Xiao, Yidong Wang, Junhao Dong, Zhenhao Kou, Jie Li, Liqun Yang, Erhu Zhao, Gregory Fonseca, Ruibang Luo, Mingyu Yang, Hongjuan Cui, Gengjie Jia, Dan Wang, Haoyang Li, Jun Ding, Zhiyuan Yuan, Haojing Shao   +26 more
wiley   +1 more source

An adversarial attack method based on pixel location characteristics

Journal of Intelligent Systems
Deep learning techniques have been widely used in various fields. However, they face significant security challenges due to the existence of adversarial examples.
Zhao Qin, Liu Jiuhong, Ma Xian, Liu Tongbo, Du Yingzhen   +4 more
doaj   +1 more source

Preparing for Tomorrow's Teamwork: Insights From eSports on How Human Expertise Shapes Training Needs for AI‐Integrated Work

Journal of Organizational Behavior, EarlyView.
ABSTRACT As organizations increasingly adopt human‐AI teams (HATs), understanding how to enhance team performance is paramount. A crucially underexplored area for supporting HATs is training, particularly helping human teammates to work with these inorganic counterparts.
Caitlin M. Lancaster, Christopher Flathmann, Jennifer Hsu, Nathan J. McNeese, Thomas A. O'Neill, Eduardo Salas   +5 more
wiley   +1 more source

Proximal Splitting Adversarial Attack for Semantic Segmentation

, 2023
International audienceClassification has been the focal point of research on adversarial attacks, but only a few works investigate methods suited to denser prediction tasks, such as semantic segmentation.
Rony, Jérôme, Ayed, Ismail Ben, Pesquet, Jean-Christophe   +2 more
core   +1 more source