Physical Hijacking Attacks against Object Trackers

dc.contributor.authorMuller, Raymonden
dc.contributor.authorMan, Yanmaoen
dc.contributor.authorCelik, Z. Berkayen
dc.contributor.authorLi, Mingen
dc.contributor.authorGerdes, Ryan M.en
dc.date.accessioned2023-02-10T18:00:59Zen
dc.date.available2023-02-10T18:00:59Zen
dc.date.issued2022-11-07en
dc.date.updated2023-01-23T15:13:31Zen
dc.description.abstractModern autonomous systems rely on both object detection and object tracking in their visual perception pipelines. Although many recent works have attacked the object detection component of autonomous vehicles, these attacks do not work on full pipelines that integrate object tracking to enhance the object detector’s accuracy. Meanwhile, existing attacks against object tracking either lack real-world applicability or do not work against a powerful class of object trackers, Siamese trackers. In this paper, we present AttrackZone, a new physically-realizable tracker hijacking attack against Siamese trackers that systematically determines valid regions in an environment that can be used for physical perturbations. AttrackZone exploits the heatmap generation process of Siamese Region Proposal Networks in order to take control of an object’s bounding box, resulting in physical consequences including vehicle collisions and masked intrusion of pedestrians into unauthorized areas. Evaluations in both the digital and physical domain show that AttrackZone achieves its attack goals 92% of the time, requiring only 0.3-3 seconds on average.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1145/3548606.3559390en
dc.identifier.urihttp://hdl.handle.net/10919/113804en
dc.language.isoenen
dc.publisherACMen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.holderThe author(s)en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titlePhysical Hijacking Attacks against Object Trackersen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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