{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/adversarial-attacks-on-variational","title":"Adversarial Attacks on Variational Autoencoders","arxiv_id":"1806.04646","date":"2018-06-12","proceeding":null,"authors":["George Gondim-Ribeiro","Pedro Tabacof","Eduardo Valle"],"abstract":"Adversarial attacks are malicious inputs that derail machine-learning models.\nWe propose a scheme to attack autoencoders, as well as a quantitative\nevaluation framework that correlates well with the qualitative assessment of\nthe attacks. We assess --- with statistically validated experiments --- the\nresistance to attacks of three variational autoencoders (simple, convolutional,\nand DRAW) in three datasets (MNIST, SVHN, CelebA), showing that both DRAW's\nrecurrence and attention mechanism lead to better resistance. As autoencoders\nare proposed for compressing data --- a scenario in which their safety is\nparamount --- we expect more attention will be given to adversarial attacks on\nthem.","url_abs":"http://arxiv.org/abs/1806.04646v1","url_pdf":"http://arxiv.org/pdf/1806.04646v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"adversarial-attacks-on-variational","repo_url":"https://github.com/gondimribeiro/adv-attacks-vae","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.04646","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}