{"id":"https://openalex.org/W4285603001","doi":"https://doi.org/10.24963/ijcai.2022/96","title":"PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning","display_name":"PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4285603001","doi":"https://doi.org/10.24963/ijcai.2022/96"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/96","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/96","pdf_url":"https://www.ijcai.org/proceedings/2022/0096.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2022/0096.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018619123","display_name":"Wei Du","orcid":"https://orcid.org/0000-0001-7289-5972"},"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":"Wei Du","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067626567","display_name":"Yichun Zhao","orcid":"https://orcid.org/0000-0001-5611-3328"},"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":"Yichun Zhao","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012994151","display_name":"Boqun Li","orcid":"https://orcid.org/0000-0003-0386-3234"},"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":"Boqun Li","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085695760","display_name":"Gongshen Liu","orcid":"https://orcid.org/0000-0001-5194-1570"},"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":"Gongshen Liu","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101717685","display_name":"Shilin Wang","orcid":"https://orcid.org/0000-0002-8214-6809"},"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":"Shilin Wang","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"680","last_page":"686"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9969000220298767,"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/T10028","display_name":"Topic Modeling","score":0.9969000220298767,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9804999828338623,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9598000049591064,"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":0.9908275604248047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8007584810256958},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7122043967247009},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6605430841445923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4507357180118561},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.42829644680023193},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3574380874633789},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07657068967819214}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9908275604248047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8007584810256958},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7122043967247009},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6605430841445923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4507357180118561},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.42829644680023193},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3574380874633789},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07657068967819214},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2022/96","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/96","pdf_url":"https://www.ijcai.org/proceedings/2022/0096.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/96","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/96","pdf_url":"https://www.ijcai.org/proceedings/2022/0096.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6499999761581421,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G7272630985","display_name":null,"funder_award_id":"U21B2020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285603001.pdf","grobid_xml":"https://content.openalex.org/works/W4285603001.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2113459411","https://openalex.org/W2160536005","https://openalex.org/W2251939518","https://openalex.org/W2748789698","https://openalex.org/W2785615365","https://openalex.org/W2896457183","https://openalex.org/W2922580172","https://openalex.org/W2943552823","https://openalex.org/W2963748441","https://openalex.org/W2965373594","https://openalex.org/W3035367371","https://openalex.org/W3098267758","https://openalex.org/W3167002899","https://openalex.org/W3174770825","https://openalex.org/W3174784402","https://openalex.org/W3205270560","https://openalex.org/W4205991051","https://openalex.org/W4288089799","https://openalex.org/W4293309189","https://openalex.org/W4299123578","https://openalex.org/W4309444617","https://openalex.org/W4312768002"],"related_works":["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","https://openalex.org/W4317672133","https://openalex.org/W4401407399"],"abstract_inverted_index":{"Recently,":[0],"prompt":[1,79,87,99],"tuning":[2],"has":[3],"shown":[4],"remarkable":[5],"performance":[6],"as":[7,54],"a":[8,63,102,134,149],"new":[9],"learning":[10],"paradigm,":[11],"which":[12],"freezes":[13],"pre-trained":[14],"language":[15],"models":[16],"(PLMs)":[17],"and":[18,82,109],"only":[19,27],"tunes":[20],"some":[21,50],"soft":[22],"prompts.":[23],"A":[24],"fixed":[25],"PLM":[26],"needs":[28],"to":[29,35,75,114],"be":[30,47,60,115],"loaded":[31],"with":[32,44,49,62,154],"different":[33,37],"prompts":[34,42],"adapt":[36],"downstream":[38,84],"tasks.":[39],"However,":[40],"the":[41,67,77,105,110,118,121,126,129,168,171,177],"associated":[43],"PLMs":[45,81],"may":[46],"added":[48],"malicious":[51],"behaviors,":[52],"such":[53],"backdoors.":[55],"The":[56,97],"victim":[57],"model":[58,131],"will":[59],"implanted":[61],"backdoor":[64],"by":[65,86,132],"using":[66],"poisoned":[68,78,98],"prompt.":[69,136,178],"In":[70],"this":[71,91,164],"paper,":[72],"we":[73],"propose":[74],"obtain":[76],"for":[80,117],"corresponding":[83],"tasks":[85,143],"tuning.":[88],"We":[89,162],"name":[90],"Poisoned":[92],"Prompt":[93],"Tuning":[94],"method":[95],"\"PPT\".":[96],"can":[100,123,147,166],"lead":[101],"shortcut":[103],"between":[104],"specific":[106],"trigger":[107],"word":[108,113],"target":[111],"label":[112],"created":[116],"PLM.":[119],"So":[120],"attacker":[122],"simply":[124],"manipulate":[125],"prediction":[127],"of":[128,170],"entire":[130],"just":[133],"small":[135],"Our":[137],"experiments":[138],"on":[139,159],"various":[140],"text":[141],"classification":[142],"show":[144],"that":[145],"PPT":[146],"achieve":[148],"99%":[150],"attack":[151],"success":[152],"rate":[153],"almost":[155],"no":[156],"accuracy":[157],"sacrificed":[158],"original":[160],"task.":[161],"hope":[163],"work":[165],"raise":[167],"awareness":[169],"possible":[172],"security":[173],"threats":[174],"hidden":[175],"in":[176]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
