Results 51 to 60 of about 94,262 (290)
Adversarial Feature Selection Against Evasion Attacks [PDF]
IEEE Transactions on Cybernetics, 2016 Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed.
Zhang F +4 more
openaire +4 more sources
Materials and System Design for Self‐Decision Bioelectronic Systems
Advanced Materials, EarlyView.This review highlights how self‐decision bioelectronic systems integrate sensing, computation, and therapy into autonomous, closed‐loop platforms that continuously monitor and treat diseases, marking a major step toward intelligent, self‐regulating healthcare technologies.
Qiankun Zeng +9 more
wiley +1 more source
Adversarial Robust and Explainable Network Intrusion Detection Systems Based on Deep Learning
Applied Sciences, 2022 The ever-evolving cybersecurity environment has given rise to sophisticated adversaries who constantly explore new ways to attack cyberinfrastructure. Recently, the use of deep learning-based intrusion detection systems has been on the rise. This rise is
Kudzai Sauka +3 more
doaj +1 more source
Jamming aided Generalized Data Attacks: Exposing Vulnerabilities in Secure Estimation
, 2015 Jamming refers to the deletion, corruption or damage of meter measurements that prevents their further usage. This is distinct from adversarial data injection that changes meter readings while preserving their utility in state estimation.
Baldick, Ross +2 more
core +1 more source
Nanozymes Integrated Biochips Toward Smart Detection System
Advanced Science, EarlyView.This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen +10 more
wiley +1 more source
Comprehensive comparisons of gradient-based multi-label adversarial attacks
Complex & Intelligent SystemsAdversarial examples which mislead deep neural networks by adding well-crafted perturbations have become a major threat to classification models. Gradient-based white-box attack algorithms have been widely used to generate adversarial examples.
Zhijian Chen +4 more
doaj +1 more source
IET Image Processing, 2023 Image recognition on deep neural network is vulnerable to adversarial sample attacks. The adversarial attack accuracy is low when only limited queries on the target are allowed with the current black box environment.
Dong Yang, Wei Chen, Songjie Wei
doaj +1 more source
Engineering Immune Cell to Counteract Aging and Aging‐Associated Diseases
Advanced Science, EarlyView.This review highlights a paradigm shift in which advanced immune cell therapies, initially developed for cancer, are now being harnessed to combat aging. By engineering immune cells to selectively clear senescent cells and remodel pro‐inflammatory tissue microenvironments, these strategies offer a novel and powerful approach to delay age‐related ...
Jianhua Guo +5 more
wiley +1 more source
Advanced Science, EarlyView.Lithium‐ion battery degradation arises from complex, localized processes during operation, limiting long‐term performance. In situ electrochemical liquid cell TEM provides unique access to these mechanisms. This review summarizes degradation phenomena revealed by liquid cell TEM, traces the evolution of the three main cell designs, compares their ...
Walid Dachraoui, Rolf Erni
wiley +1 more source
Adversarial Attacks to Manipulate Target Localization of Object Detector
IEEE AccessAdversarial attack has gradually become an important branch in the field of artificial intelligence security, where the potential threat brought by adversarial example attack is more not to be ignored.
Kai Xu +7 more
doaj +1 more source