Results 31 to 40 of about 543,217 (204)
Adversarial Patch Attack on Multi-Scale Object Detection for UAV Remote Sensing Images
Remote Sensing, 2022 Although deep learning has received extensive attention and achieved excellent performance in various scenarios, it suffers from adversarial examples to some extent. In particular, physical attack poses a greater threat than digital attack.
Yichuang Zhang +6 more
doaj +1 more source
CoRR, 2021 Adversarial attacks expose important vulnerabilities of deep learning models, yet little attention has been paid to settings where data arrives as a stream. In this paper, we formalize the online adversarial attack problem, emphasizing two key elements found in real-world use-cases: attackers must operate under partial knowledge of the target model ...
Andjela Mladenovic +6 more
openaire +3 more sources
Deflecting Adversarial Attacks
CoRR, 2020 There has been an ongoing cycle where stronger defenses against adversarial attacks are subsequently broken by a more advanced defense-aware attack. We present a new approach towards ending this cycle where we "deflect'' adversarial attacks by causing the attacker to produce an input that semantically resembles the attack's target class.
Yao Qin 0001 +4 more
openaire +2 more sources
Content-based Unrestricted Adversarial Attack [PDF]
, 2023 Unrestricted adversarial attacks typically manipulate the semantic content of an image (e.g., color or texture) to create adversarial examples that are both effective and photorealistic, demonstrating their ability to deceive human perception and deep ...
Zhang, Wenqiang +5 more
core +1 more source
Multiuser adversarial attack on deep learning for OFDM detection [PDF]
, 2022 Adversarial attack has been widely used to degrade the performance of deep learning (DL), especially in the field of communications. In this letter, we evaluate different white-box and black-box adversarial attack algorithms for a DL-based multiuser ...
Ye, Youjie, Liu, Mingqian, Chen, Yunfei
core +1 more source
Adv-Eye: A Transfer-Based Natural Eye Makeup Attack on Face Recognition
IEEE Access, 2023 Deep face recognition models are vulnerable to adversarial samples generated by adversarial attack methods. However, current attack methods do not adequately represent the security problems of the deep FR models, because they either produce adversarial ...
Jiatian Pi +6 more
doaj +1 more source
Stochastic sparse adversarial attacks [PDF]
2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), 2021 This paper introduces stochastic sparse adversarial attacks (SSAA), standing as simple, fast and purely noise-based targeted and untargeted attacks of neural network classifiers (NNC). SSAA offer new examples of sparse (or $L_0$) attacks for which only few methods have been proposed previously.
Hajri, Hatem +4 more
openaire +5 more sources
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
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 +3 more sources