{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T00:10:41Z","timestamp":1730247041451,"version":"3.28.0"},"reference-count":18,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T00:00:00Z","timestamp":1665878400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T00:00:00Z","timestamp":1665878400000},"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":[[2022,10,16]]},"DOI":"10.1109\/icip46576.2022.9897374","type":"proceedings-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T21:27:24Z","timestamp":1667510844000},"page":"1331-1335","source":"Crossref","is-referenced-by-count":0,"title":["Exploiting Doubly Adversarial Examples for Improving Adversarial Robustness"],"prefix":"10.1109","author":[{"given":"Junyoung","family":"Byun","sequence":"first","affiliation":[{"name":"Korea Advanced Institute of Science and Technology (KAIST),Republic of Korea"}]},{"given":"Hyojun","family":"Go","sequence":"additional","affiliation":[{"name":"Riiid AI Research,Republic of Korea"}]},{"given":"Seungju","family":"Cho","sequence":"additional","affiliation":[{"name":"Korea Advanced Institute of Science and Technology (KAIST),Republic of Korea"}]},{"given":"Changick","family":"Kim","sequence":"additional","affiliation":[{"name":"Korea Advanced Institute of Science and Technology (KAIST),Republic of Korea"}]}],"member":"263","reference":[{"article-title":"Intriguing properties of neural networks","year":"2013","author":"Szegedy","key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.06083"},{"key":"ref3","first-page":"2206","article-title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","volume-title":"International Conference on Machine Learning","author":"Croce"},{"article-title":"Geometry-aware instance-reweighted adversarial training","volume-title":"International Conference on Learning Representations","author":"Zhang","key":"ref4"},{"key":"ref5","first-page":"7472","article-title":"Theoretically principled trade-off between robustness and accuracy","volume-title":"International Conference on Machine Learning","author":"Zhang"},{"article-title":"Improving adversarial robustness requires revisiting misclassified examples","volume-title":"International Conference on Learning Representations","author":"Wang","key":"ref6"},{"key":"ref7","first-page":"274","article-title":"Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples","volume-title":"International Conference on Machine Learning","author":"Athalye"},{"key":"ref8","first-page":"3866","article-title":"Nattack: Learning the distributions of adversarial examples for an improved black-box attack on deep neural networks","volume-title":"International Conference on Machine Learning","author":"Li"},{"article-title":"Stochastic activation pruning for robust adversarial defense","year":"2018","author":"Dhillon","key":"ref9"},{"article-title":"Thermometer encoding: One hot way to resist adversarial examples","volume-title":"International Conference on Learning Representations","author":"Buckman","key":"ref10"},{"article-title":"A direct approach to robust deep learning using adversarial networks","year":"2019","author":"Wang","key":"ref11"},{"article-title":"The limitations of adversarial training and the blind-spot attack","year":"2019","author":"Zhang","key":"ref12"},{"key":"ref13","article-title":"Adversarial weight perturbation helps robust generalization","volume":"33","author":"Wu","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref14","article-title":"Unlabeled data improves adversarial robustness","author":"Carmon","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/591"},{"article-title":"Robustbench: a standardized adversarial robustness benchmark","year":"2020","author":"Croce","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.87"}],"event":{"name":"2022 IEEE International Conference on Image Processing (ICIP)","start":{"date-parts":[[2022,10,16]]},"location":"Bordeaux, France","end":{"date-parts":[[2022,10,19]]}},"container-title":["2022 IEEE International Conference on Image Processing (ICIP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9897158\/9897159\/09897374.pdf?arnumber=9897374","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T20:55:30Z","timestamp":1705956930000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9897374\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,16]]},"references-count":18,"URL":"https:\/\/doi.org\/10.1109\/icip46576.2022.9897374","relation":{},"subject":[],"published":{"date-parts":[[2022,10,16]]}}}