{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,15]],"date-time":"2026-08-15T16:45:25Z","timestamp":1786812325458,"version":"3.56.0"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T00:00:00Z","timestamp":1722297600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"European Union?s Horizon 2020","award":["101021797"],"award-info":[{"award-number":["101021797"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,7,30]]},"DOI":"10.1145\/3664476.3669928","type":"proceedings-article","created":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T12:35:50Z","timestamp":1721910950000},"page":"1-10","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["ARGAN-IDS: Adversarial Resistant Intrusion Detection Systems using Generative Adversarial Networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3087-1556","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Costa","sequence":"first","affiliation":[{"name":"Cybersecurity, INOV INESC Inova\u00e7\u00e3o, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2067-3232","authenticated-orcid":false,"given":"Filipe","family":"Apolin\u00e1rio","sequence":"additional","affiliation":[{"name":"Cybersecurity, INOV INESC Inova\u00e7\u00e3o, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6080-0996","authenticated-orcid":false,"given":"Carlos","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"INESC-ID, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,7,30]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/AIIoT52608.2021.9454214"},{"key":"e_1_3_2_1_2_1","volume-title":"Packet-level adversarial network traffic crafting using sequence generative adversarial networks. arXiv preprint arXiv:2103.04794","author":"Cheng Qiumei","year":"2021","unstructured":"Qiumei Cheng, Shiying Zhou, Yi Shen, Dezhang Kong, and Chunming Wu. 2021. Packet-level adversarial network traffic crafting using sequence generative adversarial networks. arXiv preprint arXiv:2103.04794 (2021)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI50451.2021.9660011"},{"key":"e_1_3_2_1_4_1","volume-title":"Generative adversarial networks: An overview","author":"Creswell Antonia","year":"2018","unstructured":"Antonia Creswell, Tom White, Vincent Dumoulin, Kai Arulkumaran, Biswa Sengupta, and Anil\u00a0A Bharath. 2018. Generative adversarial networks: An overview. IEEE signal processing magazine 35, 1 (2018), 53\u201365."},{"key":"e_1_3_2_1_5_1","volume-title":"Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572","author":"Goodfellow J","year":"2014","unstructured":"Ian\u00a0J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014. Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572 (2014)."},{"key":"e_1_3_2_1_6_1","volume-title":"On the (statistical) detection of adversarial examples. arXiv preprint arXiv:1702.06280","author":"Grosse Kathrin","year":"2017","unstructured":"Kathrin Grosse, Praveen Manoharan, Nicolas Papernot, Michael Backes, and Patrick McDaniel. 2017. On the (statistical) detection of adversarial examples. arXiv preprint arXiv:1702.06280 (2017)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3087242"},{"key":"e_1_3_2_1_8_1","volume-title":"Liuer Mihou: A Practical Framework for Generating and Evaluating Grey-box Adversarial Attacks against NIDS. arXiv preprint arXiv:2204.06113","author":"He Ke","year":"2022","unstructured":"Ke He, Dan\u00a0Dongseong Kim, Jing Sun, Jeong\u00a0Do Yoo, Young\u00a0Hun Lee, and Huy\u00a0Kang Kim. 2022. Liuer Mihou: A Practical Framework for Generating and Evaluating Grey-box Adversarial Attacks against NIDS. arXiv preprint arXiv:2204.06113 (2022)."},{"key":"e_1_3_2_1_9_1","volume-title":"Adversarial machine learning at scale. arXiv preprint arXiv:1611.01236","author":"Kurakin Alexey","year":"2016","unstructured":"Alexey Kurakin, Ian Goodfellow, and Samy Bengio. 2016. Adversarial machine learning at scale. arXiv preprint arXiv:1611.01236 (2016)."},{"key":"e_1_3_2_1_10_1","volume-title":"Artificial intelligence safety and security","author":"Kurakin Alexey","unstructured":"Alexey Kurakin, Ian\u00a0J Goodfellow, and Samy Bengio. 2018. Adversarial examples in the physical world. In Artificial intelligence safety and security. Chapman and Hall\/CRC, 99\u2013112."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.56"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134057"},{"key":"e_1_3_2_1_13_1","volume-title":"Kitsune: an ensemble of autoencoders for online network intrusion detection. arXiv preprint arXiv:1802.09089","author":"Mirsky Yisroel","year":"2018","unstructured":"Yisroel Mirsky, Tomer Doitshman, Yuval Elovici, and Asaf Shabtai. 2018. Kitsune: an ensemble of autoencoders for online network intrusion detection. arXiv preprint arXiv:1802.09089 (2018)."},{"key":"e_1_3_2_1_14_1","volume-title":"Technical report on the cleverhans v2. 1.0 adversarial examples library. arXiv preprint arXiv:1610.00768","author":"Papernot Nicolas","year":"2016","unstructured":"Nicolas Papernot, Fartash Faghri, Nicholas Carlini, Ian Goodfellow, Reuben Feinman, Alexey Kurakin, Cihang Xie, Yash Sharma, Tom Brown, Aurko Roy, 2016. Technical report on the cleverhans v2. 1.0 adversarial examples library. arXiv preprint arXiv:1610.00768 (2016)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.41"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3048038"},{"key":"e_1_3_2_1_18_1","volume-title":"Defense-gan: Protecting classifiers against adversarial attacks using generative models. arXiv preprint arXiv:1805.06605","author":"Samangouei Pouya","year":"2018","unstructured":"Pouya Samangouei, Maya Kabkab, and Rama Chellappa. 2018. Defense-gan: Protecting classifiers against adversarial attacks using generative models. arXiv preprint arXiv:1805.06605 (2018)."},{"key":"e_1_3_2_1_19_1","volume-title":"Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199","author":"Szegedy Christian","year":"2013","unstructured":"Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. 2013. Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199 (2013)."},{"key":"e_1_3_2_1_20_1","volume-title":"International Cross-Domain Conference for Machine Learning and Knowledge Extraction","author":"Teuffenbach Martin","unstructured":"Martin Teuffenbach, Ewa Piatkowska, and Paul Smith. 2020. Subverting Network Intrusion Detection: Crafting Adversarial Examples Accounting for Domain-Specific Constraints. In International Cross-Domain Conference for Machine Learning and Knowledge Extraction. Springer, 301\u2013320."},{"key":"e_1_3_2_1_21_1","volume-title":"Ensemble adversarial training: Attacks and defenses. arXiv preprint arXiv:1705.07204","author":"Tram\u00e8r Florian","year":"2017","unstructured":"Florian Tram\u00e8r, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, and Patrick McDaniel. 2017. Ensemble adversarial training: Attacks and defenses. arXiv preprint arXiv:1705.07204 (2017)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCN52240.2021.9522215"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-019-1211-x"},{"key":"e_1_3_2_1_24_1","volume-title":"Adversarial examples: Opportunities and challenges","author":"Zhang Jiliang","year":"2019","unstructured":"Jiliang Zhang and Chen Li. 2019. Adversarial examples: Opportunities and challenges. IEEE transactions on neural networks and learning systems 31, 7 (2019), 2578\u20132593."},{"key":"e_1_3_2_1_25_1","volume-title":"Generating Practical Adversarial Network Traffic Flows Using NIDSGAN. arXiv preprint arXiv:2203.06694","author":"Zolbayar Bolor-Erdene","year":"2022","unstructured":"Bolor-Erdene Zolbayar, Ryan Sheatsley, Patrick McDaniel, Michael\u00a0J Weisman, Sencun Zhu, Shitong Zhu, and Srikanth Krishnamurthy. 2022. Generating Practical Adversarial Network Traffic Flows Using NIDSGAN. arXiv preprint arXiv:2203.06694 (2022)."}],"event":{"name":"ARES 2024: The 19th International Conference on Availability, Reliability and Security","location":"Vienna Austria","acronym":"ARES 2024"},"container-title":["Proceedings of the 19th International Conference on Availability, Reliability and Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3664476.3669928","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3664476.3669928","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T16:50:19Z","timestamp":1755881419000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3664476.3669928"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,30]]},"references-count":25,"alternative-id":["10.1145\/3664476.3669928","10.1145\/3664476"],"URL":"https:\/\/doi.org\/10.1145\/3664476.3669928","relation":{},"subject":[],"published":{"date-parts":[[2024,7,30]]},"assertion":[{"value":"2024-07-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}