{"id":"https://openalex.org/W7164386745","doi":"https://doi.org/10.48550/arxiv.2606.11592","title":"Defense Against Prompt Inversion Attacks: An Information-Theoretic Approach for LLM Collaborative Inference","display_name":"Defense Against Prompt Inversion Attacks: An Information-Theoretic Approach for LLM Collaborative Inference","publication_year":2026,"publication_date":"2026-06-10","ids":{"openalex":"https://openalex.org/W7164386745","doi":"https://doi.org/10.48550/arxiv.2606.11592"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.11592","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11592","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2606.11592","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093487599","display_name":"Sayedeh Leila Noorbakhsh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Noorbakhsh, Sayedeh Leila","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138483057","display_name":"Hossein Khalili","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khalili, Hossein","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070345296","display_name":"Nader Sehatbakhsh","orcid":"https://orcid.org/0000-0001-7181-2258"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sehatbakhsh, Nader","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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.3628000020980835,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.3628000020980835,"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":0.3456000089645386,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.03880000114440918,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/inference","display_name":"Inference","score":0.705299973487854},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.6128000020980835},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6036999821662903},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.5885999798774719},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5507000088691711},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5065000057220459},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4758000075817108},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.45190000534057617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7669000029563904},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.705299973487854},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.6128000020980835},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6036999821662903},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.5885999798774719},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5507000088691711},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5065000057220459},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4758000075817108},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.45190000534057617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3580999970436096},{"id":"https://openalex.org/C2779201187","wikidata":"https://www.wikidata.org/wiki/Q2775060","display_name":"Information leakage","level":2,"score":0.3515999913215637},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35030001401901245},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.320499986410141},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31709998846054077},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2948000133037567},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C94361409","wikidata":"https://www.wikidata.org/wiki/Q7882500","display_name":"Uncertainty reduction theory","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26089999079704285},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2551000118255615},{"id":"https://openalex.org/C166088908","wikidata":"https://www.wikidata.org/wiki/Q308495","display_name":"Abductive reasoning","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.11592","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11592","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.11592","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11592","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"Collaborative":[0],"edge-cloud":[1],"inference":[2],"enables":[3],"resource-constrained":[4],"devices":[5],"to":[6,16,27,153,157],"leverage":[7],"large":[8],"language":[9],"models":[10],"(LLMs)":[11],"by":[12,84],"offloading":[13],"partial":[14],"computation":[15],"cloud":[17],"servers.":[18],"However,":[19],"transmitting":[20],"intermediate":[21,91],"activations":[22,92],"exposes":[23],"sensitive":[24],"user":[25],"prompts":[26],"prompt":[28,73,96,109],"inversion":[29,74],"attacks,":[30],"where":[31],"an":[32,68],"adversary":[33],"reconstructs":[34],"the":[35,87,94],"original":[36],"input":[37,95],"from":[38],"shared":[39],"representations.":[40],"Existing":[41],"defenses":[42,155],"rely":[43],"largely":[44],"on":[45,108,131],"heuristic":[46],"perturbations":[47],"or":[48],"empirical":[49],"tuning,":[50],"offering":[51],"limited":[52],"theoretical":[53,106],"understanding":[54],"of":[55],"privacy":[56,132],"leakage":[57],"and":[58,63,93,116,169],"its":[59],"interaction":[60],"with":[61],"utility":[62,100],"latency":[64],"constraints.":[65,103],"We":[66,104,124],"propose":[67,126],"information-theoretic":[69],"defense":[70,129],"framework":[71],"for":[72,121,167],"in":[75,160],"collaborative":[76,171],"LLM":[77,172],"inference.":[78,123,173],"Our":[79],"approach":[80],"learns":[81],"privacy-preserving":[82],"representations":[83],"explicitly":[85],"minimizing":[86],"mutual":[88],"information":[89,137],"between":[90],"while":[97],"maintaining":[98],"task":[99],"under":[101],"computational":[102],"derive":[105],"guarantees":[107],"reconstruction":[110],"error,":[111],"characterize":[112],"fundamental":[113],"privacy-utility":[114],"tradeoffs,":[115],"establish":[117],"token-level":[118],"accuracy":[119],"bounds":[120],"downstream":[122],"then":[125],"a":[127,164],"novel":[128],"based":[130],"adapters":[133],"implemented":[134],"via":[135],"low-dimensional":[136],"bottlenecks.":[138],"Extensive":[139],"experiments":[140],"across":[141],"multiple":[142],"settings":[143],"demonstrate":[144],"that":[145],"our":[146],"method":[147],"achieves":[148],"superior":[149],"privacy-utility-latency":[150],"tradeoffs":[151],"compared":[152],"existing":[154],"(up":[156],"35%":[158],"reduction":[159],"attack":[161],"success),":[162],"providing":[163],"principled":[165],"foundation":[166],"private":[168],"efficient":[170]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-12T00:00:00"}