Results 41 to 50 of about 6,497 (247)

Perceptually Constrained Adversarial Attacks

CoRR, 2021
Motivated by previous observations that the usually applied $L_p$ norms ($p=1,2,\infty$) do not capture the perceptual quality of adversarial examples in image classification, we propose to replace these norms with the structural similarity index (SSIM) measure, which was developed originally to measure the perceptual similarity of images.
Muhammad Zaid Hameed, András György 0001   +1 more
openaire   +3 more sources

Using Frequency Attention to Make Adversarial Patch Powerful Against Person Detector

IEEE Access, 2023
Deep neural networks (DNNs) are vulnerable to adversarial attacks. In particular, object detectors may be attacked by applying a particular adversarial patch to the image.
Xiaochun Lei, Xiang Cai, Chang Lu, Zetao Jiang, Zhaoting Gong, Linjun Lu   +5 more
doaj   +1 more source

Adversarial Ranking Attack and Defense [PDF]

, 2020
Deep Neural Network (DNN) classifiers are vulnerable to adversarial attack, where an imperceptible perturbation could result in misclassification. However, the vulnerability of DNN-based image ranking systems remains under-explored. In this paper, we propose two attacks against deep ranking systems, i.e., Candidate Attack and Query Attack, that can ...
Mo Zhou, Zhenxing Niu, Le Wang 0003, Qilin Zhang 0004, Gang Hua 0001   +4 more
openaire   +3 more sources

Multi-Targeted Adversarial Example in Evasion Attack on Deep Neural Network

IEEE Access, 2018
Deep neural networks (DNNs) are widely used for image recognition, speech recognition, pattern analysis, and intrusion detection. Recently, the adversarial example attack, in which the input data are only slightly modified, although not an issue for ...
Hyun Kwon, Yongchul Kim, Ki-Woong PARK, Hyunsoo Yoon, Daeseon Choi   +4 more
doaj   +1 more source

Aliasing is a Driver of Adversarial Attacks

CoRR, 2022
Aliasing is a highly important concept in signal processing, as careful consideration of resolution changes is essential in ensuring transmission and processing quality of audio, image, and video. Despite this, up until recently aliasing has received very little consideration in Deep Learning, with all common architectures carelessly sub-sampling ...
Adrián Rodríguez-Muñoz, Antonio Torralba 0001   +1 more
openaire   +3 more sources

Multi-Stage Adversarial Defense for Online DDoS Attack Detection System in IoT

IEEE Access
Machine learning-based Distributed Denial of Service (DDoS) attack detection systems have proven effective in detecting and preventing DDoD attacks in Internet of Things (IoT) systems.
Yonas Kibret Beshah, Surafel Lemma Abebe, Henock Mulugeta Melaku   +2 more
doaj   +1 more source

StackingNet: Collective Inference Across Independent AI Foundation Models

Advanced Science, EarlyView.
ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li, Chenhao Liu, Dongrui Wu, Zhigang Zeng, Lieyun Ding   +4 more
wiley   +1 more source

Time Resolved DNA Barcodes for Information Encoding and Dynamic Encryption

Advanced Science, EarlyView.
This study establishes a molecular information platform based on DNA Temporal Barcodes. Information is encoded through combinations of DNA tags with distinct retention times, while dynamic encryption is achieved through a key‐triggered DNA ligation.
Likang Chu, Haixia Wang, Haiyan Gao, Sixian Chen, Zilong Li, Zhanyihao Hao, Lei He, Da Han   +7 more
wiley   +1 more source

Care and COVID 19: Lessons for liberals and neoliberals

Child &Family Social Work, EarlyView., 2023
Abstract Within the liberal political traditions, care is regarded as a private matter, a problem of ethics rather than justice. Social justice is framed as an issue of economics (re/distribution), culture (recognition) and/or politics (representation).
Kathleen Lynch
wiley   +1 more source

Comprehensive comparisons of gradient-based multi-label adversarial attacks

Complex & Intelligent Systems
Adversarial examples which mislead deep neural networks by adding well-crafted perturbations have become a major threat to classification models. Gradient-based white-box attack algorithms have been widely used to generate adversarial examples.
Zhijian Chen, Wenjian Luo, Muhammad Luqman Naseem, Linghao Kong, Xiangkai Yang   +4 more
doaj   +1 more source