{"id":"https://openalex.org/W4402353453","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650435","title":"Sponge Backdoor Attack: Increasing the Latency of Object Detection Exploiting Non-Maximum Suppression","display_name":"Sponge Backdoor Attack: Increasing the Latency of Object Detection Exploiting Non-Maximum Suppression","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402353453","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650435"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650435","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000563958","display_name":"Yong Xiao","orcid":"https://orcid.org/0000-0001-8239-6149"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yong Xiao","raw_affiliation_strings":["Shanghai Jiao Tong University,School of Cyber Science and Engineering,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,School of Cyber Science and Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000818065","display_name":"Jin Ma","orcid":"https://orcid.org/0000-0002-9912-2520"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Ma","raw_affiliation_strings":["Shanghai Jiao Tong University,Institute of Cyber Science and Technology,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Institute of Cyber Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101382266","display_name":"Ping Yi","orcid":"https://orcid.org/0000-0003-2757-9465"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Yi","raw_affiliation_strings":["Shanghai Jiao Tong University,School of Cyber Science and Engineering,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,School of Cyber Science and Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061185006","display_name":"Xiuzhen Chen","orcid":"https://orcid.org/0000-0001-5769-7660"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuzhen Chen","raw_affiliation_strings":["Shanghai Jiao Tong University,Institute of Cyber Science and Technology,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Institute of Cyber Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000563958"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.375,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56210515,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/backdoor","display_name":"Backdoor","score":0.8943058252334595},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6563425064086914},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6156104207038879},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.45842185616493225},{"id":"https://openalex.org/keywords/sponge","display_name":"Sponge","score":0.4452284872531891},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2740864157676697},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.26946526765823364},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2501658797264099},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.145262211561203},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09509137272834778}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.8943058252334595},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6563425064086914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6156104207038879},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.45842185616493225},{"id":"https://openalex.org/C2778849931","wikidata":"https://www.wikidata.org/wiki/Q18960","display_name":"Sponge","level":2,"score":0.4452284872531891},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2740864157676697},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26946526765823364},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2501658797264099},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.145262211561203},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09509137272834778},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650435","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2037227137","https://openalex.org/W2088049833","https://openalex.org/W2126096326","https://openalex.org/W2183182206","https://openalex.org/W2193145675","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2774423163","https://openalex.org/W2942091739","https://openalex.org/W2962677013","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963769056","https://openalex.org/W2996800219","https://openalex.org/W3034414373","https://openalex.org/W3035564946","https://openalex.org/W3083185154","https://openalex.org/W3096609285","https://openalex.org/W3106250896","https://openalex.org/W3107337211","https://openalex.org/W3120052154","https://openalex.org/W3173018607","https://openalex.org/W3173694060","https://openalex.org/W3205328330","https://openalex.org/W3212735601","https://openalex.org/W3213748123","https://openalex.org/W4214680449","https://openalex.org/W4214737857","https://openalex.org/W4221145075","https://openalex.org/W4226023153","https://openalex.org/W4246399668","https://openalex.org/W4287998266","https://openalex.org/W4319301194","https://openalex.org/W4320002812","https://openalex.org/W4320736757","https://openalex.org/W4372260097","https://openalex.org/W4377241880","https://openalex.org/W4386076175","https://openalex.org/W4386076325","https://openalex.org/W4402715963","https://openalex.org/W6746897123","https://openalex.org/W6770897281","https://openalex.org/W6789325072","https://openalex.org/W6792327856","https://openalex.org/W6797626799","https://openalex.org/W6803565961","https://openalex.org/W6809873772","https://openalex.org/W6851805437"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4320031223","https://openalex.org/W4200629851","https://openalex.org/W4281902577","https://openalex.org/W4309417370","https://openalex.org/W4292107232","https://openalex.org/W3009072493","https://openalex.org/W4386080799","https://openalex.org/W3140988292"],"abstract_inverted_index":{"Backdoor":[0,62],"attacks":[1,18,35],"against":[2],"deep":[3],"learning":[4],"based":[5],"object":[6,73,84],"detectors":[7,85],"have":[8],"been":[9],"studied":[10],"increasingly":[11],"in":[12,43,82],"recent":[13],"years.":[14],"While":[15],"most":[16],"proposed":[17],"primarily":[19],"focus":[20],"on":[21,119],"compromising":[22],"the":[23,37,60,68,103,108,112],"model\u2019s":[24,38],"integrity":[25],"by":[26,90],"inducing":[27],"incorrect":[28],"detections,":[29],"only":[30],"few":[31],"studies":[32],"explore":[33],"backdoor":[34,57],"targeting":[36],"availability,":[39],"a":[40,55,78,92],"critical":[41],"concern":[42],"safety-critical":[44],"domains":[45],"such":[46],"as":[47],"autonomous":[48],"driving.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53,76,101],"introduce":[54],"novel":[56],"attack":[58],"called":[59],"Sponge":[61],"Attack":[63],"(SBA),":[64],"designed":[65],"to":[66,106],"increase":[67],"detection":[69,117],"latency":[70],"of":[71,95,111],"end-to-end":[72],"detectors.":[74],"Specifically,":[75],"overload":[77],"commonly":[79],"employed":[80],"technique":[81],"many":[83],"-":[86],"non-maximum":[87],"suppression":[88],"(NMS)":[89],"introducing":[91],"large":[93],"amount":[94],"non-existent":[96],"objects.":[97],"Through":[98],"comprehensive":[99],"experiments,":[100],"demonstrate":[102],"SBA\u2019s":[104],"effectiveness":[105],"prolong":[107],"processing":[109],"time":[110],"poisoned":[113],"image":[114],"while":[115],"maintaining":[116],"performance":[118],"clean":[120],"images":[121],"across":[122],"various":[123],"models,":[124],"datasets,":[125],"and":[126],"hardware":[127],"platforms.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
