Results 81 to 90 of about 5,389,393 (319)
Classification score approach for detecting adversarial example in deep neural network
Multimedia tools and applications, 2020 Deep neural networks (DNNs) provide superior performance on machine learning tasks such as image recognition, speech recognition, pattern analysis, and intrusion detection.
Hyun Kwon +3 more
semanticscholar +1 more source
Unauthorized AI cannot recognize me: Reversible adversarial example [PDF]
Pattern Recognition, 2018 In this study, we propose a new methodology to control how user's data is recognized and used by AI via exploiting the properties of adversarial examples.
Jiayang Liu +4 more
semanticscholar +1 more source
Weighted-Sampling Audio Adversarial Example Attack [PDF]
AAAI Conference on Artificial Intelligence, 2019 Recent studies have highlighted audio adversarial examples as a ubiquitous threat to state-of-the-art automatic speech recognition systems. Thorough studies on how to effectively generate adversarial examples are essential to prevent potential attacks ...
Xiaolei Liu +4 more
semanticscholar +1 more source
DLA: Dense-Layer-Analysis for Adversarial Example Detection [PDF]
European Symposium on Security and Privacy, 2019 In recent years Deep Neural Networks (DNNs) have achieved remarkable results and even showed superhuman capabilities in a broad range of domains. This led people to trust in DNN classifications even in security-sensitive environments like autonomous ...
Philip Sperl +3 more
semanticscholar +1 more source
Adversarial Examples Are Not Real Features
Advances in Neural Information Processing Systems 36, 2023 The existence of adversarial examples has been a mystery for years and attracted much interest. A well-known theory by \citet{ilyas2019adversarial} explains adversarial vulnerability from a data perspective by showing that one can extract non-robust features from adversarial examples and these features alone are useful for classification.
Ang Li +3 more
openaire +3 more sources
Adversarial Risk Analysis: The Somali Pirates case [PDF]
, 2013 Some of the current world’s biggest problems revolve around security issues. This has raised recent interest in resource allocation models to manage security threats, from terrorism to organized crime through money laundering.
Ríos, Jesús, Ríos Insúa, David
core
3D Printing Innovations in Polymeric Porous and Patterned Architecture
Advanced Functional Materials, EarlyView.Polymeric foams occupy a unique structural space between dense solids and open networks, where engineered void fraction governs mechanical compliance, thermal resistance, and mass transport. Additive manufacturing now enables precise spatial control over cellular architecture, unlocking designer foam structures across applications spanning crash ...
Dhanush Patil +13 more
wiley +1 more source
FADER: Fast adversarial example rejection [PDF]
, 2022 Deep neural networks are vulnerable to adversarial examples, i.e., carefully-crafted inputs that mislead classification at test time. Recent defenses have been shown to improve adversarial robustness by detecting anomalous deviations from legitimate ...
Biggio B. +4 more
core +2 more sources
Downstream-agnostic Adversarial Examples
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 This paper has been accepted by the International Conference on Computer Vision (ICCV '23, October 2--6, 2023, Paris, France)
Ziqi Zhou 0001 +6 more
openaire +2 more sources
Advanced Materials, EarlyView.This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source