{"id":"https://openalex.org/W4414943755","doi":"https://doi.org/10.48550/arxiv.2507.10886","title":"How to Protect Models against Adversarial Unlearning?","display_name":"How to Protect Models against Adversarial Unlearning?","publication_year":2025,"publication_date":"2025-07-15","ids":{"openalex":"https://openalex.org/W4414943755","doi":"https://doi.org/10.48550/arxiv.2507.10886"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2507.10886","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.10886","pdf_url":"https://arxiv.org/pdf/2507.10886","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.10886","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119896770","display_name":"Patryk Jasiorski","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jasiorski, Patryk","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069460529","display_name":"Marek Klonowski","orcid":"https://orcid.org/0000-0002-3141-8712"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Klonowski, Marek","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5060936121","display_name":"Micha\u0142 Wo\u017aniak","orcid":"https://orcid.org/0000-0003-0146-4205"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wo\u017aniak, Micha\u0142","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5119896770"],"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":0.9983999729156494,"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":0.9983999729156494,"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/adversarial-system","display_name":"Adversarial system","score":0.9021000266075134},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.8413000106811523},{"id":"https://openalex.org/keywords/phenomenon","display_name":"Phenomenon","score":0.5307999849319458},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.445499986410141},{"id":"https://openalex.org/keywords/threat-model","display_name":"Threat model","score":0.4440999925136566}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9021000266075134},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.8413000106811523},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.6507999897003174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5753999948501587},{"id":"https://openalex.org/C50335755","wikidata":"https://www.wikidata.org/wiki/Q483247","display_name":"Phenomenon","level":2,"score":0.5307999849319458},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.4440999925136566},{"id":"https://openalex.org/C2983583741","wikidata":"https://www.wikidata.org/wiki/Q16785388","display_name":"Third party","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C7606001","wikidata":"https://www.wikidata.org/wiki/Q4686702","display_name":"Adversary model","level":3,"score":0.2881999909877777},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.2651999890804291},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.25290000438690186}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2507.10886","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.10886","pdf_url":"https://arxiv.org/pdf/2507.10886","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2507.10886","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.10886","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.10886","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.10886","pdf_url":"https://arxiv.org/pdf/2507.10886","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"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":{"AI":[0,16],"models":[1],"need":[2,25],"to":[3,6,26,81,111],"be":[4,112],"unlearned":[5,137],"fulfill":[7],"the":[8,15,24,31,39,68,83,93,102,134],"requirements":[9],"of":[10,23,33,70,117,124,136],"legal":[11],"acts":[12],"such":[13,56],"as":[14,57],"Act":[17],"or":[18,36],"GDPR,":[19],"and":[20,92,106,143],"also":[21],"because":[22],"remove":[27],"toxic":[28],"content,":[29],"debiasing,":[30],"impact":[32],"malicious":[34,75],"instances,":[35],"changes":[37],"in":[38,43,60,108,133],"data":[40,110],"distribution":[41],"structure":[42],"which":[44],"a":[45,58,74,121],"model":[46,61,104,126],"works.":[47],"Unfortunately,":[48],"removing":[49],"knowledge":[50],"may":[51],"cause":[52],"undesirable":[53],"side":[54,130],"effects,":[55,131],"deterioration":[59],"performance.":[62],"In":[63],"this":[64,90,118],"paper,":[65],"we":[66],"investigate":[67],"problem":[69],"adversarial":[71],"unlearning,":[72],"where":[73],"party":[76],"intentionally":[77],"sends":[78],"unlearn":[79],"requests":[80],"deteriorate":[82],"model's":[84],"performance":[85,127],"maximally.":[86],"We":[87],"show":[88],"that":[89],"phenomenon":[91],"adversary's":[94],"capabilities":[95],"depend":[96],"on":[97,101],"many":[98],"factors,":[99],"primarily":[100],"backbone":[103],"itself":[105],"strategy/limitations":[107],"selecting":[109],"unlearned.":[113],"The":[114],"main":[115],"result":[116],"work":[119],"is":[120],"new":[122],"method":[123],"protecting":[125],"from":[128,140],"these":[129],"both":[132],"case":[135],"behavior":[138],"resulting":[139],"spontaneous":[141],"processes":[142],"adversary":[144],"actions.":[145]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
