{"id":"https://openalex.org/W7117321192","doi":"https://doi.org/10.1109/tpami.2025.3648431","title":"HGNN Shield: Defending Hypergraph Neural Networks Against High-Order Structure Attack","display_name":"HGNN Shield: Defending Hypergraph Neural Networks Against High-Order Structure Attack","publication_year":2025,"publication_date":"2025-12-26","ids":{"openalex":"https://openalex.org/W7117321192","doi":"https://doi.org/10.1109/tpami.2025.3648431","pmid":"https://pubmed.ncbi.nlm.nih.gov/41452692"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3648431","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3648431","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101819284","display_name":"Yifan Feng","orcid":"https://orcid.org/0000-0003-0878-2986"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Feng","raw_affiliation_strings":["School of Software, BNRist, THUIBCS, BLBCI, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0878-2986","affiliations":[{"raw_affiliation_string":"School of Software, BNRist, THUIBCS, BLBCI, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yifan Zhang","orcid":"https://orcid.org/0009-0006-9174-6562"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Zhang","raw_affiliation_strings":["Institute of Artificial Intelligence and Robotics, College of Artificial Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0006-9174-6562","affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, College of Artificial Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113731470","display_name":"ShaoYi DU","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoyi Du","raw_affiliation_strings":["Institute of Artificial Intelligence and Robotics, College of Artificial Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-7092-0596","affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, College of Artificial Intelligence, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063863772","display_name":"Shihui Ying","orcid":"https://orcid.org/0000-0001-9423-0146"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihui Ying","raw_affiliation_strings":["Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9423-0146","affiliations":[{"raw_affiliation_string":"Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080894318","display_name":"Jun\u2010Hai Yong","orcid":"https://orcid.org/0000-0002-4326-4167"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun-Hai Yong","raw_affiliation_strings":["School of Software, BNRist, THUIBCS, BLBCI, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4326-4167","affiliations":[{"raw_affiliation_string":"School of Software, BNRist, THUIBCS, BLBCI, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121329231","display_name":"Yue Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Gao","raw_affiliation_strings":["School of Software, BNRist, THUIBCS, BLBCI, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4971-590X","affiliations":[{"raw_affiliation_string":"School of Software, BNRist, THUIBCS, BLBCI, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.74284869,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":"4","first_page":"4205","last_page":"4221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9699000120162964,"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":0.9699000120162964,"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":0.009200000204145908,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.0020000000949949026,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/hypergraph","display_name":"Hypergraph","score":0.7757999897003174},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.667900025844574},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5802000164985657},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.426800012588501},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.3962000012397766},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38670000433921814},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.3732999861240387},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.35420000553131104}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.7757999897003174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7398999929428101},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.667900025844574},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5802000164985657},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5145000219345093},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38670000433921814},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.37779998779296875},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.3732999861240387},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3718999922275543},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.35420000553131104},{"id":"https://openalex.org/C2779312582","wikidata":"https://www.wikidata.org/wiki/Q1783272","display_name":"Counterparty","level":3,"score":0.3506999909877777},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31360000371932983},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.298799991607666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27559998631477356},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C43091099","wikidata":"https://www.wikidata.org/wiki/Q1067788","display_name":"Through-the-lens metering","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3648431","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3648431","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:41452692","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41452692","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G113806805","display_name":null,"funder_award_id":"623B2066","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2359401924","display_name":null,"funder_award_id":"L242167","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G2593274190","display_name":null,"funder_award_id":"62327808","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5841991399","display_name":null,"funder_award_id":"12531019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7091651887","display_name":null,"funder_award_id":"62021002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7619680033","display_name":null,"funder_award_id":"xtr062025010","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8008072069","display_name":null,"funder_award_id":"U24A20252","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/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W103340358","https://openalex.org/W2136179595","https://openalex.org/W2170057991","https://openalex.org/W2492695942","https://openalex.org/W2892880750","https://openalex.org/W2908442265","https://openalex.org/W2949208225","https://openalex.org/W2951823788","https://openalex.org/W2964583308","https://openalex.org/W2994598354","https://openalex.org/W2998122931","https://openalex.org/W3004507689","https://openalex.org/W3081203761","https://openalex.org/W3149040786","https://openalex.org/W3154535829","https://openalex.org/W3158396846","https://openalex.org/W3159505179","https://openalex.org/W3171412022","https://openalex.org/W3174884678","https://openalex.org/W3189215930","https://openalex.org/W3190664711","https://openalex.org/W4282926996","https://openalex.org/W4285606137","https://openalex.org/W4285806382","https://openalex.org/W4313256807","https://openalex.org/W4324125125","https://openalex.org/W4327522784","https://openalex.org/W4360616159","https://openalex.org/W4380520401","https://openalex.org/W4385270159","https://openalex.org/W4385768164","https://openalex.org/W4390818924","https://openalex.org/W4392630834","https://openalex.org/W4393641017"],"related_works":[],"abstract_inverted_index":{"Hypergraph":[0],"Neural":[1],"Networks":[2],"(HGNNs)":[3],"are":[4],"crucial":[5],"in":[6,11,142,203],"modeling":[7],"complex":[8],"high-order":[9,158],"correlations":[10],"diverse":[12],"domains,":[13],"utilizing":[14],"hyperedges":[15,66],"that":[16,167],"connect":[17],"multiple":[18],"vertices.":[19],"However,":[20],"their":[21],"susceptibility":[22],"to":[23,72,99],"structural":[24,76,159],"attacks":[25],"and":[26,33,55,67,118,126,146,173],"irrational":[27],"connections":[28],"can":[29],"disrupt":[30],"message":[31,132],"propagation":[32],"degrade":[34],"performance.":[35],"To":[36],"address":[37],"these":[38],"issues,":[39],"we":[40],"introduce":[41],"the":[42,103,138],"HGNN":[43,168,197],"Shield,":[44],"a":[45,82,153],"defense":[46,155],"framework":[47,193],"incorporating":[48],"two":[49],"key":[50],"modules:":[51],"Hyperedge-Dependent":[52],"Estimation":[53],"(HDE)":[54],"High-Order":[56],"Shield":[57,169],"(HOS).":[58],"The":[59,134],"HDE":[60],"module":[61,140],"prioritizes":[62],"vertex":[63,86],"dependencies":[64],"within":[65,88],"adapts":[68],"traditional":[69],"connectivity":[70],"measures":[71,98],"hypergraphs,":[73],"facilitating":[74],"precise":[75],"modifications.":[77],"This":[78],"adaptation":[79],"allows":[80],"for":[81],"nuanced":[83],"assessment":[84],"of":[85,111,137,187],"relationships":[87],"hyperedges,":[89],"contributing":[90],"theoretically":[91],"by":[92],"extending":[93],"classical":[94],"graph-based":[95],"connection":[96],"dependency":[97],"hypergraphs.":[100],"Following":[101],"HDE,":[102],"HOS":[104,139],"module,":[105],"positioned":[106],"before":[107],"convolutional":[108],"layers,":[109],"consists":[110],"three":[112],"submodules:":[113],"Hyperpath":[114,116,119],"Cut,":[115],"Link,":[117],"Refine.":[120],"These":[121],"components":[122],"collectively":[123],"detect,":[124],"disconnect,":[125],"refine":[127],"adversarial":[128,150],"connections,":[129],"ensuring":[130],"robust":[131],"propagation.":[133],"theoretical":[135],"contribution":[136],"lies":[141],"maintaining":[143],"hyperpath":[144],"integrity":[145,176],"learning":[147],"trajectory":[148],"under":[149],"conditions,":[151],"providing":[152],"certifiable":[154],"mechanism":[156],"against":[157,177],"attacks.":[160],"Experiments":[161],"on":[162],"six":[163],"hypergraph":[164],"datasets":[165],"indicate":[166],"significantly":[170],"enhances":[171],"robustness":[172],"maintains":[174],"data":[175],"targeted":[178],"attacks,":[179],"outperforming":[180],"existing":[181],"methods":[182],"(an":[183],"average":[184],"performance":[185],"improvement":[186],"9.33%":[188],"over":[189],"other":[190],"methods).":[191],"Our":[192],"not":[194],"only":[195],"improves":[196],"reliability":[198],"but":[199],"also":[200],"advances":[201],"security":[202],"hypergraph-based":[204],"applications.":[205]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-26T00:00:00"}
