{"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/denial-of-service-attack-on-object-detection","title":"Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors","arxiv_id":"2205.13618","date":"2022-05-26","proceeding":null,"authors":["Avishag Shapira","Alon Zolfi","Luca Demetrio","Battista Biggio","Asaf Shabtai"],"abstract":"Adversarial attacks against deep learning-based object detectors have been studied extensively in the past few years. Most of the attacks proposed have targeted the model's integrity (i.e., caused the model to make incorrect predictions), while adversarial attacks targeting the model's availability, a critical aspect in safety-critical domains such as autonomous driving, have not yet been explored by the machine learning research community. In this paper, we propose a novel attack that negatively affects the decision latency of an end-to-end object detection pipeline. We craft a universal adversarial perturbation (UAP) that targets a widely used technique integrated in many object detector pipelines -- non-maximum suppression (NMS). Our experiments demonstrate the proposed UAP's ability to increase the processing time of individual frames by adding \"phantom\" objects that overload the NMS algorithm while preserving the detection of the original objects which allows the attack to go undetected for a longer period of time.","url_abs":"https://arxiv.org/abs/2205.13618v3","url_pdf":"https://arxiv.org/pdf/2205.13618v3.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":"denial-of-service-attack-on-object-detection","repo_url":"https://github.com/avishags422/phantomsponges","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"autonomous-driving","task_name":"Autonomous Driving"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[{"method_slug":"yolo","method_name":"YOLO"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2205.13618","atlas_url":"https://app.syntology.ai/?focus=2205.13618","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.13618"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/avishags422/phantomsponges","reach":null}],"summary":{"unverified":1},"by_repo_kind":{"official":{"samples":1,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"af697e114a604c91","entry":"get_model","repo":"avishags422/phantomsponges","repo_kind":"official","path":"attack/uap_phantom_sponge.py","file_url":"https://github.com/avishags422/phantomsponges/blob/HEAD/attack/uap_phantom_sponge.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"af697e114a604c91"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}