{"id":"https://openalex.org/W7138329495","doi":"https://doi.org/10.1609/aaai.v40i29.39604","title":"GraphTextack: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs","display_name":"GraphTextack: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138329495","doi":"https://doi.org/10.1609/aaai.v40i29.39604"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i29.39604","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39604","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39604/43565","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39604/43565","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129664322","display_name":"Jiaji Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiaji Ma","raw_affiliation_strings":["University of Michigan - Ann Arbor"],"affiliations":[{"raw_affiliation_string":"University of Michigan - Ann Arbor","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127837683","display_name":"Puja Trivedi","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Puja Trivedi","raw_affiliation_strings":["University of Michigan - Ann Arbor"],"affiliations":[{"raw_affiliation_string":"University of Michigan - Ann Arbor","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129746690","display_name":"Danai Koutra","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danai Koutra","raw_affiliation_strings":["University of Michigan - Ann Arbor"],"affiliations":[{"raw_affiliation_string":"University of Michigan - Ann Arbor","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5129664322"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.54175589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"29","first_page":"24244","last_page":"24252"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9212999939918518,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9212999939918518,"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/T10028","display_name":"Topic Modeling","score":0.023600000888109207,"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":0.01769999973475933,"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":0.6040999889373779},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5831999778747559},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5388000011444092},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5214999914169312},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.32760000228881836},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.32100000977516174},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.30630001425743103}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8133000135421753},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6040999889373779},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5831999778747559},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5388000011444092},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5214999914169312},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4242999851703644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37439998984336853},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2851000130176544},{"id":"https://openalex.org/C2780741293","wikidata":"https://www.wikidata.org/wiki/Q4818019","display_name":"Attack patterns","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2728999853134155},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2533000111579895},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i29.39604","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39604","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39604/43565","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i29.39604","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39604","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39604/43565","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.44722557067871094,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138329495.pdf","grobid_xml":"https://content.openalex.org/works/W7138329495.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Text-attributed":[0],"graphs":[1],"(TAGs),":[2],"which":[3],"combine":[4],"structural":[5,57],"and":[6,31,37,67,133,162,182,191],"textual":[7],"node":[8,120],"information,":[9],"are":[10,54,62],"ubiquitous":[11],"across":[12],"many":[13,93],"domains.":[14],"Recent":[15],"work":[16],"integrates":[17],"Large":[18],"Language":[19],"Models":[20],"(LLMs)":[21],"with":[22,129,172],"Graph":[23],"Neural":[24],"Networks":[25],"(GNNs)":[26],"to":[27,56,64,135],"jointly":[28],"model":[29,137,144,148],"semantics":[30,134],"structure,":[32],"resulting":[33],"in":[34,89],"more":[35],"general":[36],"expressive":[38],"models":[39,196],"that":[40,82,177,198],"achieve":[41],"state-of-the-art":[42,193],"performance":[43],"on":[44,147,188],"TAG":[45],"benchmarks.":[46],"However,":[47],"this":[48],"integration":[49],"introduces":[50,166],"dual":[51],"vulnerabilities:":[52],"GNNs":[53],"sensitive":[55],"perturbations,":[58],"while":[59],"LLM-derived":[60],"features":[61],"vulnerable":[63],"prompt":[65],"injection":[66,121],"adversarial":[68,72],"phrasing.":[69],"While":[70],"existing":[71,94],"attacks":[73,84,95],"largely":[74],"perturb":[75],"structure":[76,132],"or":[77,103,150],"text":[78],"independently,":[79],"we":[80,113],"find":[81],"uni-modal":[83],"cause":[85],"only":[86],"modest":[87],"degradation":[88],"LLM-enhanced":[90,124,194],"GNNs.":[91,125],"Moreover,":[92],"assume":[96],"unrealistic":[97],"capabilities,":[98],"such":[99],"as":[100],"white-box":[101],"access":[102],"direct":[104],"modification":[105],"of":[106,160],"graph":[107,184],"data.":[108],"To":[109,153],"address":[110],"these":[111],"gaps,":[112],"propose":[114],"GraphTextack,":[115],"the":[116,155],"first":[117],"black-box,":[118],"multi-modal":[119],"attack":[122],"for":[123],"GraphTextack":[126,165,199],"injects":[127],"nodes":[128],"carefully":[130],"crafted":[131],"degrade":[136],"performance,":[138],"operating":[139],"under":[140],"a":[141,167,173],"realistic":[142],"threat":[143],"without":[145],"relying":[146],"internals":[149],"surrogate":[151],"models.":[152],"navigate":[154],"combinatorial,":[156],"non-differentiable":[157],"search":[158],"space":[159],"connectivity":[161],"feature":[163],"assignments,":[164],"novel":[168],"evolutionary":[169],"optimization":[170],"framework":[171],"multi-objective":[174],"fitness":[175],"function":[176],"balances":[178],"local":[179],"prediction":[180],"disruption":[181],"global":[183],"influence.":[185],"Extensive":[186],"experiments":[187],"five":[189],"datasets":[190],"two":[192],"GNN":[195],"show":[197],"significantly":[200],"outperforms":[201],"12":[202],"strong":[203],"baselines.":[204]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-03-18T00:00:00"}