{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:33:52Z","timestamp":1730266432208,"version":"3.28.0"},"reference-count":50,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,18]]},"DOI":"10.1109\/ijcnn55064.2022.9892818","type":"proceedings-article","created":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T15:56:04Z","timestamp":1664553364000},"page":"1-10","source":"Crossref","is-referenced-by-count":1,"title":["Trust-No-Pixel: A Remarkably Simple Defense against Adversarial Attacks Based on Massive Inpainting"],"prefix":"10.1109","author":[{"given":"Giorgio","family":"Ughini","sequence":"first","affiliation":[{"name":"Politecnico di Milano,Department of Electronics, Information and Bioengineering,Milan,Italy"}]},{"given":"Stefano","family":"Samele","sequence":"additional","affiliation":[{"name":"Politecnico di Milano,Department of Electronics, Information and Bioengineering,Milan,Italy"}]},{"given":"Matteo","family":"Matteucci","sequence":"additional","affiliation":[{"name":"Politecnico di Milano,Department of Electronics, Information and Bioengineering,Milan,Italy"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1561\/9781601988614"},{"key":"ref38","article-title":"Towards evaluating the robustness of neural networks","volume":"abs 1608 4644","author":"carlini","year":"2016","journal-title":"CoRR"},{"journal-title":"Deep residual learning for image recognition","year":"2015","author":"he","key":"ref33"},{"journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition","year":"2015","author":"simonyan","key":"ref32"},{"key":"ref31","article-title":"Places: A 10 million image database for scene recognition","author":"zhou","year":"2017","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"ref30","article-title":"Free-form image inpainting with gated convolution","author":"yu","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref36","article-title":"Densenet: Implementing efficient convnet descriptor pyramids","author":"iandola","year":"2014","journal-title":"ArXiv Preprint"},{"key":"ref35","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"howard","year":"2017","journal-title":"ArXiv Preprint"},{"journal-title":"Rethinking the inception architecture for computer vision","year":"2015","author":"szegedy","key":"ref34"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00577"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3072959.3073659"},{"journal-title":"Generative inpainting","year":"2018","author":"yu","key":"ref29"},{"key":"ref2","article-title":"Stochastic activation pruning for robust adversarial defense","author":"dhillon","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.41"},{"journal-title":"Exploiting the sensitivity of $l_ 2 $ adversarial examples to erase-and-restore","year":"2020","author":"zuo","key":"ref20"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00894"},{"key":"ref21","article-title":"Pixelde-fend: Leveraging generative models to understand and defend against adversarial examples","author":"song","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref24","first-page":"2672","article-title":"Generative adversarial nets","volume":"27","author":"goodfellow","year":"0","journal-title":"Advances in Neural Information Processing Systems 27"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107706"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.624"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.728"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00191"},{"journal-title":"Attacking machine learning with adversarial examples","year":"2017","author":"goodfellow","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/833"},{"journal-title":"Adversarial examples in the physical world","year":"2016","author":"kurakin","key":"ref40"},{"key":"ref12","article-title":"Mitigating adversarial effects through randomization","author":"xie","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref13","article-title":"Countering adversarial images using input transformations","author":"guo","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref14","article-title":"Feature squeezing: Detecting adversarial examples in deep neural networks","author":"xu","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00095"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-0567-8_18"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/83.862633"},{"journal-title":"Image Denoising Using Wavelets","year":"2002","author":"rangarajan","key":"ref18"},{"key":"ref19","first-page":"6707","author":"gupta","year":"2019","journal-title":"Ciidefence Defeating adversarial attacks by fusing class-specific image inpainting and image denoising"},{"key":"ref4","article-title":"Thermometer encoding: One hot way to resist adversarial examples","author":"buckman","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref3","article-title":"Ensemble adversarial training: Attacks and defenses","author":"tram\u00e8r","year":"0","journal-title":"International Conference on Learning Representations"},{"journal-title":"Explaining and Harnessing Adversarial Examples","year":"2015","author":"goodfellow","key":"ref6"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"journal-title":"Distilling the knowledge in a neural network","year":"2015","author":"hinton","key":"ref8"},{"journal-title":"Learning multiple layers of features from tiny images","year":"2009","author":"krizhevsky","key":"ref7"},{"journal-title":"On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses","year":"2018","author":"athalye","key":"ref49"},{"journal-title":"Do adversarially robust imagenet models transfer better?","year":"2020","author":"salman","key":"ref9"},{"journal-title":"Evademl-zoo","year":"0","author":"xu","key":"ref46"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.21105\/joss.02607"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"journal-title":"Obfuscated gradients give a false sense of security Circumventing defenses to adversarial examples","year":"2018","author":"athalye","key":"ref47"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00097"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"journal-title":"scikit-image","year":"0","key":"ref44"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"}],"event":{"name":"2022 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2022,7,18]]},"location":"Padua, Italy","end":{"date-parts":[[2022,7,23]]}},"container-title":["2022 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9891857\/9889787\/09892818.pdf?arnumber=9892818","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T16:52:18Z","timestamp":1665766338000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9892818\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/ijcnn55064.2022.9892818","relation":{},"subject":[],"published":{"date-parts":[[2022,7,18]]}}}