Results 21 to 30 of about 22,784,147 (354)

Black-Box Audio Adversarial Attack Using Particle Swarm Optimization

IEEE Access, 2022
The development of artificial neural networks and artificial intelligence has helped to address problems and improve services in various fields, such as autonomous driving, image classification, medical diagnosis, and speech recognition.
Hyunjun Mun, Sunggwan Seo, Baehoon Son, Joobeom Yun   +3 more
doaj   +1 more source

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

Neural 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, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin   +6 more
semanticscholar   +1 more source

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

Annual 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, Nur Imtiazul Haque, M. Rahman, M. Alonso   +3 more
semanticscholar   +1 more source

Dictionary Learning Based Scheme for Adversarial Defense in Continuous-Variable Quantum Key Distribution

Entropy, 2023
There exist various attack strategies in continuous-variable quantum key distribution (CVQKD) system in practice. Due to the powerful information processing ability of neural networks, they are applied to the detection and classification of attack ...
Shimiao Li, Pengzhi Yin, Zehao Zhou, Jianheng Tang, Duan Huang, Ling Zhang   +5 more
doaj   +1 more source

GANBA: Generative Adversarial Network for Biometric Anti-Spoofing

Applied 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, Jose A. Gonzalez-Lopez, Antonio M. Peinado   +2 more
doaj   +1 more source

DroidEnemy: Battling adversarial example attacks for Android malware detection

Digital 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, Aemun Ahmar, Wenjia Li, Fernanda Tovar, Arpit Battu, Prachi Bambarkar   +5 more
doaj   +1 more source

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

Big 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, Aminollah Khormali, Milad Salem, Jiann-Shiun Yuan   +3 more
doaj   +1 more source

Adversarial-Aware Deep Learning System Based on a Secondary Classical Machine Learning Verification Approach

Sensors, 2023
Deep learning models have been used in creating various effective image classification applications. However, they are vulnerable to adversarial attacks that seek to misguide the models into predicting incorrect classes.
Mohammed Alkhowaiter, Hisham Kholidy, Mnassar A. Alyami, Abdulmajeed Alghamdi, Cliff Zou   +4 more
doaj   +1 more source

AdvHat: Real-World Adversarial Attack on ArcFace Face ID System [PDF]

International Conference on Pattern Recognition, 2019
In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat.
Stepan Alekseevich Komkov, Aleksandr Petiushko   +1 more
semanticscholar   +1 more source

RazorNet: Adversarial Training and Noise Training on a Deep Neural Network Fooled by a Shallow Neural Network

Big Data and Cognitive Computing, 2019
In this work, we propose ShallowDeepNet, a novel system architecture that includes a shallow and a deep neural network. The shallow neural network has the duty of data preprocessing and generating adversarial samples. The deep neural network has the duty
Shayan Taheri, Milad Salem, Jiann-Shiun Yuan   +2 more
doaj   +1 more source