Results 101 to 110 of about 1,209,773 (317)

Prioritizing Feasible and Impactful Actions to Enable Secure AI Development and Use in Biology

Biotechnology and Bioengineering, EarlyView.
ABSTRACT As artificial intelligence continues to enhance biological innovation, the potential for misuse must be addressed to fully unlock the potential societal benefits. While significant work has been done to evaluate general‐purpose AI and specialized biological design tools (BDTs) for biothreat creation risks, actionable steps to mitigate the risk
Josh Dettman, Emily Lathrop, Aurelia Attal‐Juncqua, Matthew Nicotra, Allison Berke   +4 more
wiley   +1 more source

A Comprehensive Risk Analysis Method for Adversarial Attacks on Biometric Authentication Systems

IEEE Access
Recent threats to deep learning-based biometric authentication systems stem from adversarial attacks exploiting vulnerabilities in deep learning models. While existing studies extensively analyze the risk of such attacks, they primarily focus on isolated
Seong Hee Park, Soo-Hyun Lee, Min Young Lim, Pyo Min Hong, Youn Kyu Lee   +4 more
doaj   +1 more source

Advancing design strategies in smart stimulus‐responsive liposomes for drug release and nanomedicine

BMEMat, EarlyView.
Schematic illustration of stimulus‐responsive liposomes designed for controlled drug release and nanomedicine. The innermost circle represents different liposomal structures, including unilamellar, multilamellar, and multivesicular liposomes. The middle layer illustrates the responsive phospholipid components.
Yuchen Guo, Nan Li, Daiwei Zhang, Jingya Gu, Zhihuan Liao, Zihao Teng, Xiangfu Du, Peter S. Timashev, Shipeng Chen, Shuaidong Huo   +9 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, EarlyView.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Adversarial Privacy Preserving Graph Embedding against Inference Attack [PDF]

, 2020
Kaiyang Li, Guangchun Luo, Yang Ye, Wei Li, Shihao Ji, Zhipeng Cai   +5 more
openalex   +1 more source

MedRDF: A Robust and Retrain-Less Diagnostic Framework for Medical Pretrained Models Against Adversarial Attack [PDF]

, 2021
Mengting Xu, Tao Zhang, Daoqiang Zhang
openalex   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

Towards Imperceptible and Robust Adversarial Example Attacks against Neural Networks

, 2018
Machine learning systems based on deep neural networks, being able to produce state-of-the-art results on various perception tasks, have gained mainstream adoption in many applications.
Liu, Yannan, Luo, Bo, Wei, Lingxiao, Xu, Qiang   +3 more
core   +1 more source

Caught in the fire: An accidental ethnography of discomfort in researching sex work

Feminist Anthropology, EarlyView.
Abstract Drawing on fifteen years of engagement with researching Israel's sex industry, this article uses accidental ethnography to propose discomfort‐as‐method for feminist anthropology. I argue that discomfort is not a by‐product of fieldwork but a constitutive condition that disciplines researchers and shapes what can be known.
Yeela Lahav‐Raz
wiley   +1 more source