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Detection of Adversarial Attacks and Characterization of Adversarial Subspace [PDF]
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 Adversarial attacks have always been a serious threat for any data-driven model. In this paper, we explore subspaces of adversarial examples in unitary vector domain, and we propose a novel detector for defending our models trained for environmental sound classification.
Mohammad Esmaeilpour +2 more
openaire +2 more sources
On The Empirical Effectiveness of Unrealistic Adversarial Hardening Against Realistic Adversarial Attacks [PDF]
, 2023 While the literature on security attacks and defense of Machine Learning (ML) systems mostly focuses on unrealistic adversarial examples, recent research has raised concern about the under-explored field of realistic adversarial attacks and their ...
Simonetto, Thibault +6 more
core +1 more source
Remote Sensing, 2023 Deep learning (DL) models have recently been widely used in UAV aerial image semantic segmentation tasks and have achieved excellent performance. However, DL models are vulnerable to adversarial examples, which bring significant security risks to safety ...
Zhen Wang +3 more
doaj +1 more source
Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT
, 2021 As the internet continues to be populated with new devices and emerging technologies, the attack surface grows exponentially. Technology is shifting towards a profit-driven Internet of Things market where security is an afterthought.
William J. Buchanan +13 more
core +1 more source
Probabilistic Categorical Adversarial Attack & Adversarial Training
CoRR, 2022 The existence of adversarial examples brings huge concern for people to apply Deep Neural Networks (DNNs) in safety-critical tasks. However, how to generate adversarial examples with categorical data is an important problem but lack of extensive exploration.
Xu, Han +6 more
openaire +2 more sources
Functional Adversarial Attacks
CoRR, 2019 Accepted to NeurIPS ...
Cassidy Laidlaw, Soheil Feizi
openaire +3 more sources
Adversarial Attack Attribution: Discovering Attributable Signals in Adversarial ML Attacks
CoRR, 2021 Accepted to RSEML Workshop at AAAI ...
Marissa Dotter +5 more
openaire +2 more sources
Robustness of Deep Learning Models for Vision Tasks
Applied Sciences, 2023 In recent years, artificial intelligence technologies in vision tasks have gradually begun to be applied to the physical world, proving they are vulnerable to adversarial attacks.
Youngseok Lee, Jongweon Kim
doaj +1 more source
Exploring Adversarial Attacks and Defences for Fake Twitter Account Detection
, 2020 Social media has become very popular and important in people’s lives, as personal ideas, beliefs and opinions are expressed and shared through them. Unfortunately, social networks, and specifically Twitter, suffer from massive existence and perpetual ...
Nikolaos Pitropakis +7 more
core +1 more source