{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T21:28:01Z","timestamp":1730237281690,"version":"3.28.0"},"reference-count":61,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"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":[[2021,10]]},"DOI":"10.1109\/iccv48922.2021.00767","type":"proceedings-article","created":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T22:08:02Z","timestamp":1646086082000},"page":"7748-7757","source":"Crossref","is-referenced-by-count":21,"title":["Adversarial Attacks On Multi-Agent Communication"],"prefix":"10.1109","author":[{"given":"James","family":"Tu","sequence":"first","affiliation":[{"name":"Waabi"}]},{"given":"Tsunhsuan","family":"Wang","sequence":"additional","affiliation":[{"name":"MIT"}]},{"given":"Jingkang","family":"Wang","sequence":"additional","affiliation":[{"name":"Waabi"}]},{"given":"Sivabalan","family":"Manivasagam","sequence":"additional","affiliation":[{"name":"Waabi"}]},{"given":"Mengye","family":"Ren","sequence":"additional","affiliation":[{"name":"Waabi"}]},{"given":"Raquel","family":"Urtasun","sequence":"additional","affiliation":[{"name":"Waabi"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/VNC.2014.7013333"},{"article-title":"Spectral normalization for generative ad-versarial networks","year":"2018","author":"miyato","key":"ref33"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01118"},{"article-title":"Towards deep learning models resistant to adversarial attacks","year":"2017","author":"madry","key":"ref31"},{"article-title":"Towards deep learning models resistant to adversarial attacks","year":"2017","author":"madry","key":"ref30"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45023-8_44"},{"key":"ref36","article-title":"Phantom of the adas: Phantom attacks on driver-assistance systems","volume":"85","author":"nassi","year":"2020","journal-title":"IAC 2020"},{"journal-title":"Technical Report","article-title":"Bitcoin: A peer-to-peer electronic cash system","year":"2019","author":"nakamoto","key":"ref35"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2015.07.011"},{"journal-title":"ICLRE","article-title":"Freelb: Enhanced adversarial training for natural language understanding","year":"2020","author":"zhu","key":"ref60"},{"article-title":"Researchers hack bmw cars, discover 14 vulnerabilities","year":"2018","author":"zorz","key":"ref61"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00035"},{"journal-title":"CoRR","article-title":"Federated learning: Strategies for improving communication efficiency","year":"2016","author":"konecn\u00fd","key":"ref27"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"journal-title":"CoRR","article-title":"Towards federated learning at scale: System design","year":"2019","author":"bonawitz","key":"ref2"},{"key":"ref1","first-page":"634","article-title":"Analyzing federated learning through an adversarial lens","author":"bhagoji","year":"2019","journal-title":"ICML volume 97 of Proceedings of Machine Learning Research"},{"article-title":"Robust federated learning in a heterogeneous environment","year":"2019","author":"ghosh","key":"ref20"},{"journal-title":"NIPS","article-title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium","year":"2017","author":"heusel","key":"ref22"},{"journal-title":"ICLRE","article-title":"Explaining and harnessing adversarial examples","year":"2015","author":"goodfellow","key":"ref21"},{"article-title":"Adversarial attacks on neural network policies","year":"2017","author":"huang","key":"ref24"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00483"},{"journal-title":"CoRR","article-title":"Federated learning: Strategies for improving communication efficiency","year":"2016","author":"konecn\u00fd","key":"ref26"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351088"},{"article-title":"Towards physically realistic adversarial examples for lidar object detection","year":"2020","author":"tu","key":"ref50"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ACSSC.2018.8645472"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00284"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.153"},{"journal-title":"ICLR OpenReview net","article-title":"DBA: distributed backdoor attacks against federated learning","year":"2020","author":"xie","key":"ref56"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1187"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1080\/08839510050144886"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018973"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58536-5_36"},{"volume":"3","article-title":"Hopskipjumpattack: A query-efficient decision-based attack","year":"2019","author":"chen","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/SP40000.2020.00045"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM.2016.7795300"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3128572.3140448"},{"journal-title":"ICLRE","article-title":"Query-efficient hard-label black-box attack: An optimization-based approach","year":"2019","author":"cheng","key":"ref13"},{"journal-title":"CoRR","article-title":"Seq2sick: Evaluating the robustness of sequence-to-sequence models with adversarial examples","year":"2018","author":"cheng","key":"ref14"},{"journal-title":"NeurIPS","article-title":"Geometry-aware recurrent neural networks for active visual recognition","year":"2018","author":"cheng","key":"ref15"},{"journal-title":"NeurIPS","article-title":"Improving black-box adversarial attacks with a transfer-based prior","year":"2019","author":"cheng","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/AINA.2010.187"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3194554.3194565"},{"key":"ref19","first-page":"1605","article-title":"Local model poisoning attacks to byzantine-robust federated learning","author":"fang","year":"2020","journal-title":"USENIX Security Symposium"},{"journal-title":"ICLRE","article-title":"Decision-based adversarial attacks: Reliable attacks against black-box machine learning models","year":"2018","author":"brendel","key":"ref4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1049\/ecej:20020504"},{"journal-title":"CoRR","article-title":"Guessing smart: Biased sampling for efficient black-box adversarial attacks","year":"2018","author":"brunner","key":"ref6"},{"article-title":"Watch chinese hackers control tesla’s brakes from 12 miles away","year":"2016","author":"brewster","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3339815"},{"journal-title":"ICLR (Poster) OpenReview net","article-title":"Robustness may be at odds with accuracy","year":"2019","author":"tsipras","key":"ref49"},{"article-title":"ShapeNet: An Information-Rich 3D Model Repository","year":"2015","author":"chang","key":"ref9"},{"article-title":"Capital one breach high-lights shortfalls of encryption","year":"2019","author":"stupp","key":"ref46"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2015.02.018"},{"journal-title":"ICLRE","article-title":"Intriguing properties of neural networks","year":"2014","author":"szegedy","key":"ref48"},{"key":"ref47","first-page":"877","article-title":"Towards robust lidar-based perception in autonomous driving: General black-box adversarial sensor attack and countermeasures","author":"sun","year":"2020","journal-title":"Usenix Security"},{"journal-title":"VTC","article-title":"V2v communications in automotive multi-sensor multi-target tracking","year":"2008","author":"rockl","key":"ref42"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2012.6232130"},{"journal-title":"IJCAI","article-title":"Interpretable adversarial perturbation in input em-bedding space for text","year":"2018","author":"sato","key":"ref44"},{"journal-title":"MICCAI","article-title":"U-net: Convolutional networks for biomedical image segmentation","year":"2015","author":"ronneberger","key":"ref43"}],"event":{"name":"2021 IEEE\/CVF International Conference on Computer Vision (ICCV)","start":{"date-parts":[[2021,10,10]]},"location":"Montreal, QC, Canada","end":{"date-parts":[[2021,10,17]]}},"container-title":["2021 IEEE\/CVF International Conference on Computer Vision (ICCV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9709627\/9709628\/09711249.pdf?arnumber=9711249","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T19:43:02Z","timestamp":1657741382000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9711249\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10]]},"references-count":61,"URL":"https:\/\/doi.org\/10.1109\/iccv48922.2021.00767","relation":{},"subject":[],"published":{"date-parts":[[2021,10]]}}}