{"id":"https://openalex.org/W7155809746","doi":"https://doi.org/10.48550/arxiv.2604.22550","title":"ArmSSL: Adversarial Robust Black-Box Watermarking for Self-Supervised Learning Pre-trained Encoders","display_name":"ArmSSL: Adversarial Robust Black-Box Watermarking for Self-Supervised Learning Pre-trained Encoders","publication_year":2026,"publication_date":"2026-04-24","ids":{"openalex":"https://openalex.org/W7155809746","doi":"https://doi.org/10.48550/arxiv.2604.22550"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.22550","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22550","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2604.22550","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134738147","display_name":"Yongqi Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yongqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134672092","display_name":"Yansong Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Yansong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134714565","display_name":"Boyu Kuang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuang, Boyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134736130","display_name":"Chunyi Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Chunyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134709943","display_name":"Anmin Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Anmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134687327","display_name":"Liquan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Liquan","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":0.9440000057220459,"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":0.9440000057220459,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.014600000344216824,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.010400000028312206,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/watermark","display_name":"Watermark","score":0.9168000221252441},{"id":"https://openalex.org/keywords/digital-watermarking","display_name":"Digital watermarking","score":0.8808000087738037},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.727400004863739},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6003000140190125},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5412999987602234},{"id":"https://openalex.org/keywords/orthogonality","display_name":"Orthogonality","score":0.45750001072883606},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4156000018119812},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.373199999332428}],"concepts":[{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.9168000221252441},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.8808000087738037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7666000127792358},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.727400004863739},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6003000140190125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5648000240325928},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5412999987602234},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.45750001072883606},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4472000002861023},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3513999879360199},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.29319998621940613},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C182548165","wikidata":"https://www.wikidata.org/wiki/Q2261483","display_name":"Scrambling","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28040000796318054},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.26579999923706055},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.2572999894618988},{"id":"https://openalex.org/C2780581891","wikidata":"https://www.wikidata.org/wiki/Q15738686","display_name":"Copy protection","level":4,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.22550","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22550","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2604.22550","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22550","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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],"encoders":[3,38],"are":[4,39],"invaluable":[5],"intellectual":[6],"property":[7],"(IP).":[8],"However,":[9],"no":[10],"existing":[11],"SSL":[12,67,212],"watermarking":[13,68],"for":[14],"IP":[15],"protection":[16],"can":[17],"concurrently":[18],"satisfy":[19],"the":[20,36,54,91,106,122,146,149,176,188,193,200],"following":[21],"two":[22],"practical":[23],"requirements:":[24],"(1)":[25],"provide":[26],"ownership":[27,229],"verification":[28,101],"capability":[29],"under":[30,47],"black-box":[31,72,104],"suspect":[32,107],"model":[33],"access":[34],"once":[35],"stolen":[37],"used":[40],"in":[41,103],"downstream":[42],"tasks;":[43],"(2)":[44],"be":[45,179],"robust":[46],"adversarial":[48,75,110,239],"watermark":[49,55,95,128,143,153,159,169,177],"detection":[50,240],"or":[51],"removal,":[52],"because":[53],"samples":[56,160],"form":[57],"a":[58,99,139,167,182],"distinguishable":[59],"out-of-distribution":[60],"(OOD)":[61],"cluster.":[62],"We":[63],"propose":[64],"ArmSSL,":[65],"an":[66],"framework":[69],"that":[70,225],"assures":[71],"verifiability":[73],"and":[74,93,117,154,214,234,241],"robustness":[76,236],"while":[77,145],"preserving":[78],"utility.":[79],"For":[80,109,165],"verification,":[81,230],"we":[82],"introduce":[83],"paired":[84],"discrepancy":[85,151],"enlargement,":[86],"enforcing":[87],"feature-space":[88],"orthogonality":[89],"between":[90,152],"clean":[92,131,155,202],"its":[94],"counterpart":[96],"to":[97,120,136,174,178],"produce":[98],"reliable":[100],"signal":[102],"against":[105,237],"model.":[108],"robustness,":[111],"ArmSSL":[112,226],"integrates":[113],"latent":[114],"representation":[115],"entanglement":[116],"distribution":[118],"alignment":[119],"suppress":[121],"OOD":[123],"clustering.":[124],"The":[125],"former":[126],"entangles":[127],"representations":[129,132],"with":[130,197,219,222],"(i.e.,":[133],"from":[134],"non-source-class)":[135],"avoid":[137],"forming":[138],"dense":[140],"cluster":[141],"of":[142,199],"samples,":[144],"latter":[147],"minimizes":[148],"distributional":[150],"representations,":[156],"thereby":[157],"disguising":[158],"as":[161,181],"natural":[162],"in-distribution":[163],"data.":[164,206],"utility,":[166],"reference-guided":[168],"tuning":[170],"strategy":[171],"is":[172],"designed":[173],"allow":[175],"learned":[180],"small":[183],"side":[184],"task":[185,190],"without":[186],"affecting":[187],"main":[189],"by":[191],"aligning":[192],"watermarked":[194],"encoder's":[195],"outputs":[196],"those":[198],"original":[201],"encoder":[203],"on":[204],"normal":[205],"Extensive":[207],"experiments":[208],"across":[209],"five":[210],"mainstream":[211],"frameworks":[213],"nine":[215],"benchmark":[216],"datasets,":[217],"along":[218],"end-to-end":[220],"comparisons":[221],"SOTAs,":[223],"demonstrate":[224],"achieves":[227],"superior":[228],"negligible":[231],"utility":[232],"degradation,":[233],"strong":[235],"various":[238],"removal.":[242]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-28T00:00:00"}
