{"id":"https://openalex.org/W7133517779","doi":"https://doi.org/10.48550/arxiv.2603.02849","title":"DSBA: Dynamic Stealthy Backdoor Attack with Collaborative Optimization in Self-Supervised Learning","display_name":"DSBA: Dynamic Stealthy Backdoor Attack with Collaborative Optimization in Self-Supervised Learning","publication_year":2026,"publication_date":"2026-03-03","ids":{"openalex":"https://openalex.org/W7133517779","doi":"https://doi.org/10.48550/arxiv.2603.02849"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.02849","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02849","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.02849","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128066556","display_name":"Jiayao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jiayao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127899016","display_name":"Mohammad Maruf Hasan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hasan, Mohammad Maruf","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035931692","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-8794-4332"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yiping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121303786","display_name":"Xiaoying Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei, Xiaoying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128064993","display_name":"Jiale Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jiale","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089198043","display_name":"Qilin Wu","orcid":"https://orcid.org/0000-0002-4559-9315"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Qilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124966199","display_name":"Junwu Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Junwu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128102552","display_name":"Dongfang Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Dongfang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8733000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.8733000159263611,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.021800000220537186,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.016899999231100082,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/backdoor","display_name":"Backdoor","score":0.9693999886512756},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5302000045776367},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4043000042438507},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.38940000534057617},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.349700003862381},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.34049999713897705}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9693999886512756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7383999824523926},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5302000045776367},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4043000042438507},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.35019999742507935},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.33709999918937683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32100000977516174},{"id":"https://openalex.org/C3309286","wikidata":"https://www.wikidata.org/wiki/Q4907693","display_name":"Bilevel optimization","level":3,"score":0.31869998574256897},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2578999996185303},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.02849","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02849","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.02849","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02849","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Self-Supervised":[0],"Learning":[1],"(SSL)":[2],"has":[3],"emerged":[4],"as":[5,58],"a":[6,84,92,114,138],"significant":[7],"paradigm":[8],"in":[9,49,69,173],"representation":[10],"learning":[11],"thanks":[12],"to":[13,16,42,124,142,166,182],"its":[14,22,27],"ability":[15],"learn":[17],"without":[18],"extensive":[19],"labeled":[20],"data,":[21],"strong":[23],"generalization":[24],"capabilities,":[25],"and":[26,65,78,157,171,193,207,214],"potential":[28],"for":[29,118,148],"privacy":[30],"preservation.":[31],"However,":[32],"recent":[33],"research":[34],"reveals":[35],"that":[36],"SSL":[37,51,191],"models":[38],"are":[39],"also":[40,161],"vulnerable":[41],"backdoor":[43,46,115,127],"attacks.":[44],"Existing":[45],"attack":[47,76,103,169],"methods":[48],"the":[50,102,110,134],"context":[52],"commonly":[53],"suffer":[54],"from":[55],"issues":[56],"such":[57],"high":[59],"detectability":[60],"of":[61,73],"triggers,":[62],"feature":[63,120,155],"entanglement,":[64],"pronounced":[66],"out-of-distribution":[67],"properties":[68],"poisoned":[70],"samples,":[71,150],"all":[72],"which":[74,174],"compromises":[75],"effectiveness":[77],"stealthiness.":[79],"To":[80],"that,":[81],"we":[82,95,175],"propose":[83],"Dynamic":[85],"Stealthy":[86],"Backdoor":[87],"Attack":[88,203],"(DSBA)":[89],"backed":[90],"by":[91],"new":[93],"technique":[94],"term":[96],"Collaborative":[97],"Optimization.":[98],"This":[99],"method":[100],"decouples":[101],"process":[104],"into":[105],"two":[106],"collaborative":[107],"optimization":[108,112,136],"layers:":[109],"outer-layer":[111],"trains":[113],"encoder":[116],"responsible":[117],"global":[119],"space":[121,156],"remodeling,":[122],"aiming":[123],"achieve":[125],"precise":[126],"implantation":[128],"while":[129,209],"preserving":[130],"core":[131],"functionality;":[132],"meanwhile,":[133],"inner-layer":[135],"employs":[137],"dynamically":[139,167],"optimized":[140],"generator":[141],"adaptively":[143],"produce":[144],"optimally":[145],"concealed":[146],"triggers":[147],"individual":[149],"achieving":[151],"coordinated":[152],"concealment":[153],"across":[154],"visual":[158],"space.":[159],"We":[160],"introduce":[162],"multiple":[163],"loss":[164],"functions":[165],"balance":[168],"performance":[170],"stealthiness,":[172],"employ":[176],"an":[177],"adaptive":[178],"weight":[179],"scheduling":[180],"mechanism":[181],"enhance":[183],"training":[184],"stability.":[185],"Extensive":[186],"experiments":[187],"on":[188],"various":[189],"mainstream":[190,222],"algorithms":[192],"five":[194],"public":[195],"datasets":[196],"demonstrate":[197],"that:":[198],"(i)":[199],"DSBA":[200,216],"significantly":[201],"enhances":[202],"Success":[204],"Rate":[205],"(ASR)":[206],"stealthiness":[208],"maintaining":[210],"downstream":[211],"task":[212],"accuracy;":[213],"(ii)":[215],"exhibits":[217],"superior":[218],"robustness":[219],"against":[220],"existing":[221],"defense":[223],"methods.":[224]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-05T00:00:00"}