{"id":"https://openalex.org/W7160657247","doi":"https://doi.org/10.48550/arxiv.2605.05534","title":"Adversarial Graph Neural Network Benchmarks: Towards Practical and Fair Evaluation","display_name":"Adversarial Graph Neural Network Benchmarks: Towards Practical and Fair Evaluation","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160657247","doi":"https://doi.org/10.48550/arxiv.2605.05534"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.05534","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05534","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2605.05534","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111233212","display_name":"Tran Gia Bao Ngo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ngo, Tran Gia Bao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082090877","display_name":"Zulfikar Alom","orcid":"https://orcid.org/0000-0002-4073-0476"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alom, Zulfikar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084297425","display_name":"Federico Errica","orcid":"https://orcid.org/0000-0001-5181-2904"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Errica, Federico","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135639953","display_name":"Murat Kantarcioglu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kantarcioglu, Murat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5045418504","display_name":"C\u00fcneyt G\u00fcrcan Ak\u00e7ora","orcid":"https://orcid.org/0000-0002-2882-6950"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akcora, Cuneyt Gurcan","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.8884000182151794,"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":0.8884000182151794,"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":0.07699999958276749,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.006800000090152025,"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":0.9585000276565552},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5618000030517578},{"id":"https://openalex.org/keywords/adversarial-machine-learning","display_name":"Adversarial machine learning","score":0.4733999967575073},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4172999858856201},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.39489999413490295},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38190001249313354}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9585000276565552},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6913999915122986},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5813999772071838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5677000284194946},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5618000030517578},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.4733999967575073},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4172999858856201},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.39489999413490295},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38190001249313354},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3109999895095825},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2904999852180481},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26820001006126404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.05534","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05534","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2605.05534","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05534","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Adversarial":[0],"learning":[1,18],"and":[2,28,71,87,105,112,144,159],"the":[3,16,23,46,59,64,81,160,164,175,185],"robustness":[4,47],"of":[5,12,25,38,48,83,100,163,177],"Graph":[6],"Neural":[7],"Networks":[8],"(GNNs)":[9],"are":[10],"topics":[11],"widespread":[13],"interest":[14],"in":[15,50,58,91,135,191],"machine":[17,194],"community,":[19],"as":[20,155],"documented":[21],"by":[22],"number":[24],"adversarial":[26,40,92,136,192],"attacks":[27,104],"defenses":[29,108],"designed":[30],"for":[31,188],"these":[32,39],"purposes.":[33],"While":[34],"a":[35,97,128,142,168],"rigorous":[36],"evaluation":[37,89],"methods":[41],"is":[42],"necessary":[43],"to":[44,69,174],"understand":[45],"GNNs":[49],"real-world":[51],"applications,":[52],"we":[53,79],"posit":[54],"that":[55,150],"many":[56],"works":[57],"literature":[60],"do":[61],"not":[62],"share":[63],"same":[65],"experimental":[66],"settings,":[67],"leading":[68],"ambiguous":[70],"potentially":[72],"contradictory":[73],"scientific":[74],"conclusions.":[75],"In":[76],"this":[77],"benchmark,":[78],"demonstrate":[80],"importance":[82],"adopting":[84],"fair,":[85],"robust,":[86],"standardized":[88,189],"protocols":[90],"GNN":[93],"research.":[94],"We":[95,131],"perform":[96],"comprehensive":[98],"re-evaluation":[99],"seven":[101],"widely":[102],"used":[103],"eight":[106],"recent":[107],"under":[109,141],"both":[110],"poisoning":[111],"evasion":[113],"scenarios,":[114],"across":[115],"six":[116],"popular":[117],"graph":[118,193],"datasets.":[119],"Our":[120,147],"study":[121],"spans":[122],"over":[123],"453,000":[124],"experiments":[125],"conducted":[126],"within":[127],"unified":[129],"framework.":[130],"observe":[132],"substantial":[133],"differences":[134],"attack":[137,172],"performance":[138,180],"when":[139],"evaluated":[140],"fair":[143],"robust":[145],"procedure.":[146],"findings":[148],"reveal":[149],"previously":[151],"overlooked":[152],"factors,":[153],"such":[154],"target":[156],"node":[157],"selection":[158],"training":[161],"process":[162],"attacked":[165],"model,":[166],"have":[167],"profound":[169],"impact":[170],"on":[171],"effectiveness,":[173],"extent":[176],"completely":[178],"distorting":[179],"insights.":[181],"These":[182],"results":[183],"underscore":[184],"urgent":[186],"need":[187],"evaluations":[190],"learning.":[195]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-09T00:00:00"}