Results 31 to 40 of about 82,924 (315)

Defending Against Adversarial Fingerprint Attacks Based on Deep Image Prior

IEEE Access, 2023
Recently, deep learning-based biometric authentication systems, especially fingerprint authentication, have been used widely in real-world. However, these systems are vulnerable to adversarial attacks which prevent deep learning models from ...
Hwajung Yoo, Pyo Min Hong, Taeyong Kim, Jung Won Yoon, Youn Kyu Lee   +4 more
doaj   +1 more source

Certified Defenses for Adversarial Patches

CoRR, 2020
International Conference on Learning Representations, ICLR ...
Chiang, Ping-yeh, Ni, Renkun, Abdelkader, Ahmed, Zhu, Chen, Studer, Christoph; id_orcid0000-0001-8950-6267, Goldstein, Tom   +5 more
openaire   +4 more sources

Deepfake Cross-Model Defense Method Based on Generative Adversarial Network [PDF]

Jisuanji gongcheng
To reduce social risks caused by the abuse of deepfake technology, an active defense method against deep forgery based on a Generative Adversarial Network (GAN) is proposed. Adversarial samples are created by adding imperceptible perturbation to original
DAI Lei, CAO Lin, GUO Yanan, ZHANG Fan, DU Kangning
doaj   +1 more source

Scaling provable adversarial defenses

CoRR, 2018
Recent work has developed methods for learning deep network classifiers that are provably robust to norm-bounded adversarial perturbation; however, these methods are currently only possible for relatively small feedforward networks. In this paper, in an effort to scale these approaches to substantially larger models, we extend previous work in three ...
Eric Wong 0001, Frank R. Schmidt, Jan Hendrik Metzen, J. Zico Kolter   +3 more
openaire   +3 more sources

Adversarial Attacks and Defenses in Deep Learning

Engineering, 2020
With the rapid developments of artificial intelligence (AI) and deep learning (DL) techniques, it is critical to ensure the security and robustness of the deployed algorithms.
Kui Ren, Tianhang Zheng, Zhan Qin, Xue Liu   +3 more
doaj   +1 more source

An American Advantage? How American and Swiss Criminal Defense Attorneys Evaluate Forensic DNA Evidence [PDF]

, 2016
Critics of the American system of justice sometimes perceive “inquisitorialism” as an attractive alternative. In this article we will report a comparative study investigating the way forensic DNA evidence is handled in criminal prosecutions in the Swiss ...
Thompson, William C, Vuille, Joelle
core   +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

Leveraging linear mapping for model-agnostic adversarial defense

Frontiers in Computer Science, 2023
In the ever-evolving landscape of deep learning, novel designs of neural network architectures have been thought to drive progress by enhancing embedded representations.
Huma Jamil, Yajing Liu, Nathaniel Blanchard, Michael Kirby, Michael Kirby, Chris Peterson   +5 more
doaj   +1 more source

Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks

, 2020
Deep neural networks (DNN) are known to be vulnerable to adversarial attacks. Numerous efforts either try to patch weaknesses in trained models, or try to make it difficult or costly to compute adversarial examples that exploit them.
Li, Bo, Shan, Shawn, Wang, Bolun, Wenger, Emily, Zhao, Ben Y., Zheng, Haitao   +5 more
core   +1 more source

Adversarial Robustness Enhancement of UAV-Oriented Automatic Image Recognition Based on Deep Ensemble Models

Remote Sensing, 2023
Deep neural networks (DNNs) have been widely utilized in automatic visual navigation and recognition on modern unmanned aerial vehicles (UAVs), achieving state-of-the-art performances.
Zihao Lu, Hao Sun, Yanjie Xu
doaj   +1 more source