Results 61 to 70 of about 6,980 (145)

RLXSS: Optimizing XSS Detection Model to Defend Against Adversarial Attacks Based on Reinforcement Learning

Future Internet, 2019
With the development of artificial intelligence, machine learning algorithms and deep learning algorithms are widely applied to attack detection models. Adversarial attacks against artificial intelligence models become inevitable problems when there is a
Yong Fang, Cheng Huang, Yijia Xu, Yang Li   +3 more
doaj   +1 more source

Using art history to explore society's changing connections with agriculture

PLANTS, PEOPLE, PLANET, EarlyView.
Food insecurity is a looming challenge that especially affects those least fortunate. Consumer food choices have a substantial impact on the sustainability of current food systems. Here, we use art as a lens through which to consider our contemporary and historical relationship to one of the world's most crucial crops, the potato, in the context of the
Edward F. Hill‐King, Martin R. McAinsh, Michael R. Roberts   +2 more
wiley   +1 more source

Multimodal artificial intelligence in medical biotechnology: Integrating genomics, imaging, and clinical data for precision therapeutics

Precision Medical Sciences, EarlyView.
Overview of multimodal artificial intelligence (AI) for precision therapeutics. Diverse biomedical data modalities, including multi‐omics, medical imaging, digital pathology, electronic health records, wearable‐device data, and molecular information, are integrated through multimodal AI frameworks incorporating fusion strategies, foundation models ...
Gedion Mengistu Dejen
wiley   +1 more source

Black-Box Universal Adversarial Attack for DNN-Based Models of SAR Automatic Target Recognition

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Synthetic aperture radar automatic target recognition (SAR-ATR) models based on deep neural networks (DNNs) are vulnerable to attacks of adversarial examples. Universal adversarial attack algorithms can help evaluate and improve the robustness of the SAR-
Xuanshen Wan, Wei Liu, Chaoyang Niu, Wanjie Lu, Meng Du, Yuanli Li   +5 more
doaj   +1 more source

Neural Network‐Based Runtime Monitoring and Control for Unknown Nonlinear Systems

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Real‐time system monitoring and stabilization become especially challenging when the system dynamics are unknown. This article introduces a novel design for monitoring and stabilizing unknown nonlinear systems with measurement noise. The design utilizes a generic modelling framework by decomposing the system into a known tunable linear ...
Jianglin Lan, Xianxian Zhao, Ron Patton
wiley   +1 more source

Research on adversarial attack and defense of photovoltaic power prediction

Dianzi Jishu Yingyong
Deep neural networks have been widely used in photovoltaic power prediction, but they are vulnerable to adversarial attacks. In order to improve the robustness of the prediction model, an adversarial attack algorithm based on fast gradient sign method ...
Zhou Wang
doaj   +1 more source

Generative AI‐Driven Supply Chain Digital Innovation: Enabling Integration, Resilience, and Sustainable Business Value Creation

Sustainable Development, EarlyView.
ABSTRACT In today's volatile, uncertain, complex, and ambiguous (VUCA) business environment, organizations face mounting pressure to develop agile and resilient supply chains capable of withstanding increasingly frequent disruptions. At the same time, sustainability has evolved into a strategic necessity, requiring firms to balance competitiveness with
Arsalan Zahid Piprani, Sajid Nazir, Mahmood Ali, Sumona Mukhuty, Jyri Vilko   +4 more
wiley   +1 more source

Integrating multimodal data and machine learning for entrepreneurship research

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley   +1 more source

Adversarial Attacks Against World Models: Hallucination-Driven Policy Failure

Applied Sciences
World models have demonstrated powerful environment modeling capabilities in scenarios such as autonomous driving and robotics, but their adversarial security issues remain underexplored, in particular, adversarial risk analysis of world models.
Junjian Zhang, Hao Tan, Ruonan Li, Aiping Li, Zhaoquan Gu   +4 more
doaj   +1 more source

Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions

Software: Practice and Experience, EarlyView.
ABSTRACT Context The rapid increase in cyber threats, coupled with increasingly sophisticated attack strategies and the exponential growth of data in recent years, has exposed significant limitations in classical machine learning, rule‐based, and signature‐based defense mechanisms.
Siva Sai, Ishika Goyal, Shubham Sharma, Sri Harshita Manuri, Vinay Chamola, Rajkumar Buyya   +5 more
wiley   +1 more source