{"id":"https://openalex.org/W4414816323","doi":"https://doi.org/10.32604/cmc.2025.068590","title":"A Novel Unsupervised Structural Attack and Defense for Graph Classification","display_name":"A Novel Unsupervised Structural Attack and Defense for Graph Classification","publication_year":2025,"publication_date":"2025-10-04","ids":{"openalex":"https://openalex.org/W4414816323","doi":"https://doi.org/10.32604/cmc.2025.068590"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.068590","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.068590","pdf_url":"https://cdn.techscience.press/files/cmc/2025/TSP_CMC-86-1/TSP_CMC_68590/TSP_CMC_68590.pdf","source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://cdn.techscience.press/files/cmc/2025/TSP_CMC-86-1/TSP_CMC_68590/TSP_CMC_68590.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062802890","display_name":"Yadong Wang","orcid":"https://orcid.org/0009-0005-2430-6439"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yadong Wang","raw_affiliation_strings":["School of Computer Science & Technology, Beijing Institute of Technology, Beijing, 100081, China 2 School of Computing, Institute of Science Tokyo, Tokyo, 152-8550, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Beijing Institute of Technology, Beijing, 100081, China 2 School of Computing, Institute of Science Tokyo, Tokyo, 152-8550, Japan","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100347591","display_name":"Zhiwei Zhang","orcid":"https://orcid.org/0000-0001-9257-4092"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Zhang","raw_affiliation_strings":["School of Computer Science & Technology, Beijing Institute of Technology, Beijing, 100081, China 2 School of Computing, Institute of Science Tokyo, Tokyo, 152-8550, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Beijing Institute of Technology, Beijing, 100081, China 2 School of Computing, Institute of Science Tokyo, Tokyo, 152-8550, Japan","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039733842","display_name":"Pengpeng Qiao","orcid":"https://orcid.org/0000-0002-2428-8737"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengpeng Qiao","raw_affiliation_strings":["School of Computer Science & Technology, Beijing Institute of Technology, Beijing, 100081, China 2 School of Computing, Institute of Science Tokyo, Tokyo, 152-8550, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Beijing Institute of Technology, Beijing, 100081, China 2 School of Computing, Institute of Science Tokyo, Tokyo, 152-8550, Japan","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054991337","display_name":"Guoren Wang","orcid":"https://orcid.org/0000-0002-0181-8379"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoren Wang","raw_affiliation_strings":["School of Computer Science & Technology, Beijing Institute of Technology, Beijing, 100081, China 2 School of Computing, Institute of Science Tokyo, Tokyo, 152-8550, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Beijing Institute of Technology, Beijing, 100081, China 2 School of Computing, Institute of Science Tokyo, Tokyo, 152-8550, Japan","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13696583,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"86","issue":"1","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9449999928474426,"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":0.9449999928474426,"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/graph","display_name":"Graph","score":0.6021000146865845},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.46619999408721924},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.36899998784065247},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.3513999879360199},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.3269999921321869},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.32019999623298645},{"id":"https://openalex.org/keywords/graph-property","display_name":"Graph property","score":0.2955999970436096},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.2703000009059906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7070000171661377},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6021000146865845},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.46619999408721924},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4345000088214874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42309999465942383},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40869998931884766},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.36899998784065247},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3513999879360199},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.314300000667572},{"id":"https://openalex.org/C64339825","wikidata":"https://www.wikidata.org/wiki/Q722659","display_name":"Graph property","level":5,"score":0.2955999970436096},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C106937863","wikidata":"https://www.wikidata.org/wiki/Q7236518","display_name":"Power graph analysis","level":3,"score":0.26589998602867126},{"id":"https://openalex.org/C2777522414","wikidata":"https://www.wikidata.org/wiki/Q648457","display_name":"Social graph","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.068590","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.068590","pdf_url":"https://cdn.techscience.press/files/cmc/2025/TSP_CMC-86-1/TSP_CMC_68590/TSP_CMC_68590.pdf","source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.068590","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.068590","pdf_url":"https://cdn.techscience.press/files/cmc/2025/TSP_CMC-86-1/TSP_CMC_68590/TSP_CMC_68590.pdf","source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1130084210","display_name":null,"funder_award_id":"2024YFE0209000","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1391239753","display_name":null,"funder_award_id":"2024YFE0209000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4794527876","display_name":null,"funder_award_id":"U23B2019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8837258941","display_name":null,"funder_award_id":"U23B2019","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320323110","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414816323.pdf","grobid_xml":"https://content.openalex.org/works/W4414816323.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Graph":[0,254,262],"Neural":[1],"Networks":[2],"(GNNs)":[3],"have":[4],"proven":[5],"highly":[6],"effective":[7],"for":[8,81],"graph":[9,28,82,107,114,144,218],"classification":[10,45,219],"across":[11,266],"diverse":[12],"fields":[13],"such":[14,67,175],"as":[15],"social":[16],"networks,":[17],"bioinformatics,":[18],"and":[19,150,206,226,235,258,292],"finance,":[20],"due":[21],"to":[22,25,37,56,111,162,172,188,228,277],"their":[23,32,44,62],"capability":[24],"learn":[26,112],"complex":[27],"structures.":[29,145],"However,":[30],"despite":[31],"success,":[33],"GNNs":[34],"remain":[35],"vulnerable":[36],"adversarial":[38,48],"attacks":[39],"that":[40,136,184,270],"can":[41],"significantly":[42],"degrade":[43],"accuracy.":[46],"Existing":[47],"attack":[49,79,196,234,240],"strategies":[50],"primarily":[51],"rely":[52],"on":[53,88,143,214,252,260],"label":[54,89],"information":[55,68],"guide":[57],"the":[58,123,128,138,154,160,164,167,190,230,244,253,261,285],"attacks,":[59],"which":[60,84],"limits":[61],"applicability":[63,94],"in":[64,95,247],"scenarios":[65],"where":[66],"is":[69,185],"scarce":[70],"or":[71],"unavailable.":[72],"This":[73],"paper":[74],"introduces":[75],"an":[76,133,239],"innovative":[77],"unsupervised":[78,272],"method":[80,103,273],"classification,":[83],"operates":[85],"without":[86],"relying":[87],"information,":[90],"thereby":[91],"enhancing":[92],"its":[93],"a":[96,106,179],"broad":[97],"range":[98],"of":[99,122,140,166,232,242,289],"scenarios.":[100],"Specifically,":[101],"our":[102,195,233,271,282],"first":[104],"leverages":[105],"contrastive":[108],"learning":[109],"loss":[110],"high-quality":[113],"embeddings":[115],"by":[116,159,194,202],"comparing":[117],"different":[118,267],"stochastic":[119],"augmented":[120],"views":[121],"graphs.":[124],"To":[125],"effectively":[126],"perturb":[127],"graphs,":[129],"we":[130,177],"then":[131],"introduce":[132],"implicit":[134],"estimator":[135],"measures":[137],"impact":[139],"various":[141],"modifications":[142],"The":[146],"proposed":[147],"strategy":[148],"identifies":[149],"flips":[151],"edges":[152],"with":[153],"top-K":[155],"highest":[156,286],"scores,":[157],"determined":[158],"estimator,":[161],"maximize":[163],"degradation":[165,275],"model\u2019s":[168],"performance.":[169],"In":[170],"addition,":[171],"defend":[173],"against":[174,298],"attack,":[176],"propose":[178],"lightweight":[180],"regularization-based":[181],"defense":[182,236,283],"mechanism":[183],"specifically":[186],"tailored":[187],"mitigate":[189],"structural":[191,299],"perturbations":[192],"introduced":[193],"strategy.":[197],"It":[198],"enhances":[199],"model":[200,248],"robustness":[201,297],"enforcing":[203],"embedding":[204],"consistency":[205],"edge-level":[207],"smoothness":[208],"during":[209],"training.":[210],"We":[211],"conduct":[212],"experiments":[213],"six":[215],"public":[216],"TU":[217],"datasets:":[220],"NCI1,":[221],"NCI109,":[222],"Mutagenicity,":[223],"ENZYMES,":[224],"COLLAB,":[225],"DBLP_v1,":[227],"evaluate":[229],"effectiveness":[231],"strategies.":[237],"Under":[238],"budget":[241],"3,":[243],"maximum":[245],"reduction":[246],"accuracy":[249,287],"reaches":[250],"6.67%":[251],"Convolutional":[255],"Network":[256,264],"(GCN)":[257,291],"11.67%":[259],"Attention":[263],"(GAT)":[265],"datasets,":[268],"indicating":[269],"induces":[274],"comparable":[276],"state-of-the-art":[278],"supervised":[279],"attacks.":[280],"Meanwhile,":[281],"achieves":[284],"recovery":[288],"3.89%":[290],"5.00%":[293],"(GAT),":[294],"demonstrating":[295],"improved":[296],"perturbations.":[300]},"counts_by_year":[],"updated_date":"2026-06-25T06:16:34.145877","created_date":"2025-10-10T00:00:00"}