Results 91 to 100 of about 6,341 (246)

Stop Using Limiting Stimuli as a Measure of Sensitivities of Energetic Materials

Propellants, Explosives, Pyrotechnics, EarlyView.
ABSTRACT Accurately estimating the sensitivity of explosive materials is a potentially life‐saving task that requires standardised protocols across nations. One of the most widely applied procedures worldwide is the so‐called ‘1‐In‐6’ test from the United Nations (UN) Manual of Tests in Criteria, which estimates a ‘limiting stimulus’ for a material. In
Dennis Christensen, Geir Petter Novik
wiley   +1 more source

Llm-ga: A gradient-based multi-label adversarial attack by large language models

Complex & Intelligent Systems
Deep neural networks (DNNs) are highly sensitive to small, meticulously crafted perturbations, which have been utilized in adversarial attacks, threatening the reliability of DNNs in practical applications. Current adversarial attack methods rely heavily
Yujiang Liu, Yamin Hu, Zhijian Chen, Shiyin Wang, Wenjian Luo   +4 more
doaj   +1 more source

Physically structured adversarial patch inspired by natural leaves multiply angles deceives infrared detectors

Journal of King Saud University: Computer and Information Sciences
Researching infrared adversarial attacks is crucial for ensuring the safe deployment of security-sensitive systems reliant on infrared object detectors.
Zhiyang Hu, Xing Yang, Jiwen Zhao, Haoqi Gao, Haoli Xu, Hua Mu, Yangyang Wang   +6 more
doaj   +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

DIPA: Adversarial Attack on DNNs by Dropping Information and Pixel-Level Attack on Attention

Information
Deep neural networks (DNNs) have shown remarkable performance across a wide range of fields, including image recognition, natural language processing, and speech processing. However, recent studies indicate that DNNs are highly vulnerable to well-crafted
Jing Liu, Huailin Liu, Pengju Wang, Yang Wu, Keqin Li   +4 more
doaj   +1 more source

Adversarial Attacks on Hyperbolic Networks

As hyperbolic deep learning grows in popularity, so does the need for adversarial robustness in the context of such a non-Euclidean geometry. To this end, this paper proposes hyperbolic alternatives to the commonly used FGM and PGD adversarial attacks.
Max van Spengler, Jan Zahálka, Pascal Mettes   +2 more
openaire   +2 more sources

Mathematical Analysis of Adversarial Attacks

CoRR, 2018
In this paper, we analyze efficacy of the fast gradient sign method (FGSM) and the Carlini-Wagner's L2 (CW-L2) attack. We prove that, within a certain regime, the untargeted FGSM can fool any convolutional neural nets (CNNs) with ReLU activation; the targeted FGSM can mislead any CNNs with ReLU activation to classify any given image into any prescribed
Zehao Dou, Stanley J. Osher, Bao Wang 0001   +2 more
openaire   +2 more sources

Physical Unclonable Function Based on 3D‐NAND Flash Array Structure With Multi‐Chip Implementation

Small, EarlyView.
Physical unclonable function (PUF) based on a 3D‐NAND flash array is proposed, featuring a multi‐chip structure and a massive challenge–response pair (CRP) capacity. The presented utilizes intrinsic string current variations experimentally verified across eight fabricated 48 × 24 NAND flash arrays.
Hwiho Hwang, Sangwook Youn, Jinwoo Park, Dayeon Yu, Hyungjin Kim   +4 more
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

Generative AI—the Transgression of Technology

Systems Research and Behavioral Science, EarlyView.
ABSTRACT This article offers a systems‐theoretical analysis of generative artificial intelligence (GenAI) grounded in Niklas Luhmann's sociology of technology. It addresses a central conceptual problem: How GenAI can be understood within a theoretical framework that has traditionally defined technology as a means of stabilising action through causal ...
Jesper Tække
wiley   +1 more source