{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T16:33:31Z","timestamp":1759336411596,"version":"3.40.3"},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T00:00:00Z","timestamp":1726790400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T00:00:00Z","timestamp":1726790400000},"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":[[2024,9,20]]},"DOI":"10.1109\/icmlc63072.2024.10935037","type":"proceedings-article","created":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T02:39:19Z","timestamp":1743129559000},"page":"579-584","source":"Crossref","is-referenced-by-count":1,"title":["Deep Generative Models as an Adversarial Attack Strategy for Tabular Machine Learning"],"prefix":"10.1109","author":[{"given":"Salijona","family":"Dyrmishi","sequence":"first","affiliation":[{"name":"University of Luxembourg,Luxembourg"}]},{"given":"Mihaela C\u0103t\u0103lina","family":"Stoian","sequence":"additional","affiliation":[{"name":"University of Oxford,United Kingdom"}]},{"given":"Eleonora","family":"Giunchiglia","sequence":"additional","affiliation":[{"name":"Imperial College London,United Kingdom"}]},{"given":"Maxime","family":"Cordy","sequence":"additional","affiliation":[{"name":"University of Luxembourg,Luxembourg"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1007\/11538059_91"},{"key":"ref2","article-title":"DECAF: generating fair synthetic data using causally-aware generative networks","volume-title":"Proceedings of Neural Information Processing Systems","author":"Van Breugel","year":"2021"},{"key":"ref3","article-title":"Invertible tabular GANs: Killing two birds with one stone for tabu-lar data synthesis","volume-title":"Proceedings of Neural Information Processing Systems","author":"Lee","year":"2021"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.24963\/ijcai.2018\/543"},{"key":"ref5","article-title":"How realistic is your synthetic data? constraining deep generative models for tabular data","volume-title":"The Twelfth International Conference on Learning Representations","author":"Stoian","year":"2024"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1016\/j.procs.2021.04.118"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1109\/IWCMC.2019.8766353"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1007\/978-3-031-05981-0_7"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1007\/978-981-19-8991-9_29"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.14778\/3231751.3231757"},{"key":"ref11","article-title":"Modeling tabular data using conditional GAN","volume-title":"Proceedings of Neural Information Processing Systems","author":"Xu","year":"2019"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1145\/3442381.3449999"},{"year":"2018","author":"Xie","journal-title":"Dif-ferentially private generative adversarial network","key":"ref13"},{"key":"ref14","article-title":"PATE-GAN: generating synthetic data with differential privacy guar-antees","volume-title":"Proceedings of International Conference on Learning Representations","author":"Jordon","year":"2019"},{"key":"ref15","article-title":"TabDDPM: Modelling Tabular Data with Diffusion Models","volume-title":"Proceedings of International Con-ference on Machine Learning","author":"Kotelnikov","year":"2023"},{"key":"ref16","article-title":"STaSy: Score-based Tabular data Synthesis","volume-title":"Proceedings of International Conference on Learning Representations","author":"Kim","year":"2023"},{"key":"ref17","article-title":"GOGGLE: Generative modelling for tabular data by learning relational structure","volume-title":"Proceedings of International Conference on Learning Representations","author":"Liu","year":"2022"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1109\/ICCVW.2019.00257"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1109\/ICIP42928.2021.9506278"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/ICCVW54120.2021.00021"},{"key":"ref21","article-title":"Constructing unrestricted adversarial examples with generative models","author":"Song","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref22","article-title":"Ex-ploiting t-norms for deep learning in autonomous driving","volume-title":"Proceedings of the International Workshop on Neural-Symbolic Learning and Reasoning","author":"Stoian","year":"2023"},{"year":"2023","author":"Simonetto","journal-title":"Constrained adaptive attacks: Realistic evaluation of adversarial examples and robust training of deep neural networks for tabular data","key":"ref23"},{"key":"ref24","article-title":"Wasserstein GAN","author":"Arjovsky","year":"2017","journal-title":"CoRR"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.24963\/ijcai.2022\/183"}],"event":{"name":"2024 International Conference on Machine Learning and Cybernetics (ICMLC)","start":{"date-parts":[[2024,9,20]]},"location":"Miyazaki, Japan","end":{"date-parts":[[2024,9,23]]}},"container-title":["2024 International Conference on Machine Learning and Cybernetics (ICMLC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10934982\/10934998\/10935037.pdf?arnumber=10935037","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,29]],"date-time":"2025-03-29T02:07:33Z","timestamp":1743214053000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10935037\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,20]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/icmlc63072.2024.10935037","relation":{},"subject":[],"published":{"date-parts":[[2024,9,20]]}}}