{"id":"https://openalex.org/W7140093171","doi":"https://doi.org/10.18653/v1/2026.findings-eacl.29","title":"VortexPIA: Indirect Prompt Injection Attack against LLMs for Efficient Extraction of User Privacy","display_name":"VortexPIA: Indirect Prompt Injection Attack against LLMs for Efficient Extraction of User Privacy","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7140093171","doi":"https://doi.org/10.18653/v1/2026.findings-eacl.29"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-eacl.29","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-eacl.29","pdf_url":"https://aclanthology.org/2026.findings-eacl.29.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-eacl.29.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130387646","display_name":"Yu Yan Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Cui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130345559","display_name":"Sicheng Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sicheng Pan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130341212","display_name":"Yifei Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifei Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130334186","display_name":"Haibin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haibin Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5060586262","display_name":"Cong Zuo","orcid":"https://orcid.org/0000-0001-9464-7216"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cong Zuo","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":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"587","last_page":"609"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11424","display_name":"Security and Verification in Computing","score":0.14329999685287476,"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/T11424","display_name":"Security and Verification in Computing","score":0.14329999685287476,"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/T10237","display_name":"Cryptography and Data Security","score":0.10289999842643738,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.0681999996304512,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4537000060081482},{"id":"https://openalex.org/keywords/privacy-protection","display_name":"Privacy protection","score":0.4514000117778778},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2948000133037567},{"id":"https://openalex.org/keywords/confidentiality","display_name":"Confidentiality","score":0.28279998898506165},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.2669999897480011}],"concepts":[{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.6452000141143799},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5878999829292297},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.4652000069618225},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4537000060081482},{"id":"https://openalex.org/C3017597292","wikidata":"https://www.wikidata.org/wiki/Q25052250","display_name":"Privacy protection","level":2,"score":0.4514000117778778},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3059000074863434},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C71745522","wikidata":"https://www.wikidata.org/wiki/Q2476929","display_name":"Confidentiality","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C527821871","wikidata":"https://www.wikidata.org/wiki/Q228502","display_name":"Access control","level":2,"score":0.2483000010251999}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-eacl.29","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-eacl.29","pdf_url":"https://aclanthology.org/2026.findings-eacl.29.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-eacl.29","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-eacl.29","pdf_url":"https://aclanthology.org/2026.findings-eacl.29.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2580860177","display_name":null,"funder_award_id":"62272043","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"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7140093171.pdf","grobid_xml":"https://content.openalex.org/works/W7140093171.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"been":[5],"widely":[6],"deployed":[7],"in":[8,40,61,77,97,117],"Conversational":[9],"AIs":[10],"(CAIs),":[11],"while":[12],"exposing":[13],"privacy":[14,75,95,162],"and":[15,140,154,167],"security":[16,35],"threats.Recent":[17],"research":[18],"shows":[19],"that":[20,41,48,93,149],"LLM-based":[21],"CAIs":[22],"can":[23,50,69],"be":[24],"manipulated":[25],"to":[26,59,112,124],"extract":[27],"private":[28,115],"information":[29,116],"from":[30],"human":[31],"users,":[32],"posing":[33],"serious":[34],"threats.However,":[36],"the":[37,53],"methods":[38],"proposed":[39],"study":[42],"rely":[43],"on":[44,134,176],"a":[45,66,87],"white-box":[46],"setting":[47],"adversaries":[49],"directly":[51],"modify":[52],"system":[54],"prompt.This":[55],"condition":[56],"is":[57],"unlikely":[58],"hold":[60],"real-world":[62],"deployments.The":[63],"limitation":[64],"raises":[65],"critical":[67],"question:":[68],"unprivileged":[70],"attackers":[71,123],"still":[72],"induce":[73],"such":[74],"risks":[76],"practical":[78,184],"LLM-integrated":[79,98,180],"applications?To":[80],"address":[81],"this":[82],"question,":[83],"we":[84],"propose":[85],"VORTEXPIA,":[86],"novel":[88],"indirect":[89],"prompt":[90],"injection":[91],"attack":[92],"induces":[94],"extraction":[96],"applications":[99],"under":[100],"black-box":[101],"settings.By":[102],"injecting":[103],"token-efficient":[104],"data":[105],"containing":[106],"false":[107],"memories,":[108],"VORTEXPIA":[109,133,150,175],"misleads":[110],"LLMs":[111],"actively":[113],"request":[114],"batches.Unlike":[118],"prior":[119],"methods,":[120],"VORTEX-PIA":[121],"allows":[122],"flexibly":[125],"define":[126],"multiple":[127,177],"categories":[128],"of":[129],"sensitive":[130],"data.We":[131],"evaluate":[132],"six":[135],"LLMs,":[136,142],"covering":[137],"both":[138],"traditional":[139],"reasoning":[141],"across":[143],"four":[144],"benchmark":[145],"datasets.The":[146],"results":[147],"show":[148],"significantly":[151],"outperforms":[152],"baselines":[153],"achieves":[155],"state-of-the-art":[156],"(SOTA)":[157],"performance.It":[158],"also":[159],"demonstrates":[160],"efficient":[161],"requests,":[163],"reduced":[164],"token":[165],"consumption,":[166],"enhanced":[168],"robustness":[169],"against":[170],"defense":[171],"mechanisms.We":[172],"further":[173],"validate":[174],"realistic":[178],"open-source":[179],"applications,":[181],"demonstrating":[182],"its":[183],"effectiveness.":[185]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-24T00:00:00"}
