Results 21 to 30 of about 24,885,017 (322)

Untargeted white-box adversarial attack to break into deep leaning based COVID-19 monitoring face mask detection system

open access: yesMultimedia tools and applications, 2023
The face mask detection system has been a valuable tool to combat COVID-19 by preventing its rapid transmission. This article demonstrated that the present deep learning-based face mask detection systems are vulnerable to adversarial attacks. We proposed
Burhan ul haque Sheikh, Aasim Zafar
semanticscholar   +1 more source

On Evaluating Adversarial Robustness of Large Vision-Language Models [PDF]

open access: yesNeural Information Processing Systems, 2023
Large vision-language models (VLMs) such as GPT-4 have achieved unprecedented performance in response generation, especially with visual inputs, enabling more creative and adaptable interaction than large language models such as ChatGPT.
Yunqing Zhao   +6 more
semanticscholar   +1 more source

Hierarchical Adversarial Attacks Against Graph-Neural-Network-Based IoT Network Intrusion Detection System

open access: yesIEEE Internet of Things Journal, 2022
The advancement of Internet of Things (IoT) technologies leads to a wide penetration and large-scale deployment of IoT systems across an entire city or even country.
Xiaokang Zhou   +5 more
semanticscholar   +1 more source

Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection [PDF]

open access: yesComputer Vision and Pattern Recognition, 2022
This study addresses the issue of fusing infrared and visible images that appear differently for object detection. Aiming at generating an image of high visual quality, previous approaches discover commons underlying the two modalities and fuse upon the ...
Jinyuan Liu   +6 more
semanticscholar   +1 more source

GANBA: Generative Adversarial Network for Biometric Anti-Spoofing

open access: yesApplied Sciences, 2022
Automatic speaker verification (ASV) is a voice biometric technology whose security might be compromised by spoofing attacks. To increase the robustness against spoofing attacks, presentation attack detection (PAD) or anti-spoofing systems for detecting ...
Alejandro Gomez-Alanis   +2 more
doaj   +1 more source

G-IDS: Generative Adversarial Networks Assisted Intrusion Detection System [PDF]

open access: yesAnnual International Computer Software and Applications Conference, 2020
The boundaries of cyber-physical systems (CPS) and the Internet of Things (IoT) are converging together day by day to introduce a common platform on hybrid systems.
Md Hasan Shahriar   +3 more
semanticscholar   +1 more source

DroidEnemy: Battling adversarial example attacks for Android malware detection

open access: yesDigital Communications and Networks, 2022
In recent years, we have witnessed a surge in mobile devices such as smartphones, tablets, smart watches, etc., most of which are based on the Android operating system. However, because these Android-based mobile devices are becoming increasingly popular,
Neha Bala   +5 more
doaj   +1 more source

Resilient Distributed Energy Management for Systems of Interconnected Microgrids [PDF]

open access: yes, 2018
In this paper, distributed energy management of interconnected microgrids, which is stated as a dynamic economic dispatch problem, is studied. Since the distributed approach requires cooperation of all local controllers, when some of them do not comply ...
Ananduta, Wicak   +3 more
core   +2 more sources

Does the Adversarial System Truly Deliver Justice in South Africa? A Critical Analysis [PDF]

open access: yesE-Journal of Humanities, Arts and Social Sciences
A pillar of South Africa’s legal system, the adversarial system places a strong emphasis on party-driven litigation in which competing parties argue their positions before an impartial judge.
Ntsika Qakaza
doaj   +1 more source

Developing a Robust Defensive System against Adversarial Examples Using Generative Adversarial Networks

open access: yesBig Data and Cognitive Computing, 2020
In this work, we propose a novel defense system against adversarial examples leveraging the unique power of Generative Adversarial Networks (GANs) to generate new adversarial examples for model retraining. To do so, we develop an automated pipeline using
Shayan Taheri   +3 more
doaj   +1 more source

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