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....
@InProceedings{advrank, title={Adversarial Ranking Attack and Defense}, author={Zhou, Mo and Niu, Zhenxing and Wang, Le and Zhang, Qilin and Hua, Gang}, booktitle={ECCV}, year={2020}, pages={781--799}, isbn={978-3-030-58568-6} } Bibtex for the ArXiv preprint version: @article...
Evaluation processes include systematic ranking, Sensitivity Analysis, and Explainability Analysis, employing the LIME algorithm. These diverse elements collectively contribute to the distinctiveness of the study in the context of VANETs and adversarial attack detection. The structure of the paper is as ...
Christian Szegedy et al. firstly found that the highly accurate modern deep learning models are susceptible to adversarial samples that are derived from the original images by adding small perturbations. To address the security problem of AI system, many methods for model attack and defense have bee...
Must-read Papers on Textual Adversarial Attack and Defense (TAAD) This list is currently maintained by Chenghao Yang at UChicago. Other previous main contributors including Fanchao Qi, and Yuan Zang when they were at THUNLP. We thank all the great contributors very much. Contents 0. Toolkits ...
The modiication is exactly for the defense towards the attack of imposter samples. By using this regularization, the generated imposters are more trending to be far away from target classes and have equal chances of being non-target. We call the modiied regularization in Eq. (6) as label...
11. Bridging Maximum Likelihood and Adversarial Learning via α-Divergence 会议:AAAI 2020. AAAI Technical Track: Machine Learning. 作者:Miaoyun Zhao, Yulai Cong, Shuyang Dai, Lawrence Carin 链接:https://aaai.org/ojs/index.php/AAAI/article/view/6172/6028 ...
to seize positions in the queue, and the randomization will influence more in a degradation of the service quality than in the attack effects mitigation... Gabriel Macia-Fernandez,Jesus E. Diaz-Verdejo,Pedro Garcia-Teodoro - 《Computers & Security》 被引量: 0发表: 2008年 Defense Against Adve...
2018Adversarial Personalized Ranking for RecommendationAttack/DefenseBPR-MFSIGIRLinkCode ADVERSARIAL LEARNING FOR GAN-BASED RECOMMENDATION This page is managed and maintained by: Releases No releases published Packages No packages published
Our code is based on the public code of the following paper:"Adversarial Attack and Defense in Deep Ranking" arXiv: 2106.03614. download and prepare datasets as described inREADME.md. generate python configurations for the models by runningbash tools/autogen.bash. ...