{"id":"https://openalex.org/W7134225921","doi":"https://doi.org/10.3390/e28030308","title":"Strong Target Attack on Hypergraph Neural Networks via Label Poisoning and Structure Modification","display_name":"Strong Target Attack on Hypergraph Neural Networks via Label Poisoning and Structure Modification","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134225921","doi":"https://doi.org/10.3390/e28030308","pmid":"https://pubmed.ncbi.nlm.nih.gov/41899960"},"language":"en","primary_location":{"id":"doi:10.3390/e28030308","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28030308","pdf_url":"https://www.mdpi.com/1099-4300/28/3/308/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/28/3/308/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128416029","display_name":"Jie Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139779","display_name":"Yantai Nanshan University","ror":"https://ror.org/0499b1896","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210139779"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Huang","raw_affiliation_strings":["College of Technology and Data, Yantai Nanshan University, Yantai 265713, China"],"raw_orcid":"https://orcid.org/0009-0006-1714-589X","affiliations":[{"raw_affiliation_string":"College of Technology and Data, Yantai Nanshan University, Yantai 265713, China","institution_ids":["https://openalex.org/I4210139779"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010945146","display_name":"Qinke Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139779","display_name":"Yantai Nanshan University","ror":"https://ror.org/0499b1896","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210139779"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiaoyan Sun","raw_affiliation_strings":["College of Intelligent Science and Engineering, Yantai Nanshan University, Yantai 265713, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligent Science and Engineering, Yantai Nanshan University, Yantai 265713, China","institution_ids":["https://openalex.org/I4210139779"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128622412","display_name":"Na Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139779","display_name":"Yantai Nanshan University","ror":"https://ror.org/0499b1896","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210139779"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Zhang","raw_affiliation_strings":["College of Technology and Data, Yantai Nanshan University, Yantai 265713, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Technology and Data, Yantai Nanshan University, Yantai 265713, China","institution_ids":["https://openalex.org/I4210139779"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128479635","display_name":"Meizhu Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139779","display_name":"Yantai Nanshan University","ror":"https://ror.org/0499b1896","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210139779"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meizhu Zheng","raw_affiliation_strings":["College of Technology and Data, Yantai Nanshan University, Yantai 265713, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Technology and Data, Yantai Nanshan University, Yantai 265713, China","institution_ids":["https://openalex.org/I4210139779"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210139779"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27153096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":"3","first_page":"308","last_page":"308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.5519999861717224,"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":0.5519999861717224,"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":0.19609999656677246,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.08219999819993973,"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/hypergraph","display_name":"Hypergraph","score":0.64410001039505},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4526999890804291},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.4408000111579895},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43389999866485596},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.40939998626708984},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4090000092983246},{"id":"https://openalex.org/keywords/associative-property","display_name":"Associative property","score":0.4074000120162964},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4052000045776367},{"id":"https://openalex.org/keywords/subsequence","display_name":"Subsequence","score":0.37959998846054077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7699999809265137},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.64410001039505},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4526999890804291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4449000060558319},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.4408000111579895},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4226999878883362},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.40939998626708984},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4090000092983246},{"id":"https://openalex.org/C159423971","wikidata":"https://www.wikidata.org/wiki/Q177251","display_name":"Associative property","level":2,"score":0.4074000120162964},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4052000045776367},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40230000019073486},{"id":"https://openalex.org/C137877099","wikidata":"https://www.wikidata.org/wiki/Q1332977","display_name":"Subsequence","level":3,"score":0.37959998846054077},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.37070000171661377},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3246999979019165},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C2780267512","wikidata":"https://www.wikidata.org/wiki/Q6997828","display_name":"Nestedness","level":3,"score":0.26460000872612},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e28030308","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28030308","pdf_url":"https://www.mdpi.com/1099-4300/28/3/308/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:41899960","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41899960","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:3f2be210836d427fa1db21fb7dd436fa","is_oa":true,"landing_page_url":"https://doaj.org/article/3f2be210836d427fa1db21fb7dd436fa","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 28, Iss 3, p 308 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13025657","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13025657/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e28030308","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28030308","pdf_url":"https://www.mdpi.com/1099-4300/28/3/308/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.46071264147758484,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7134225921.pdf","grobid_xml":"https://content.openalex.org/works/W7134225921.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W2162630660","https://openalex.org/W2168190036","https://openalex.org/W2803831897","https://openalex.org/W3042321348","https://openalex.org/W3085990079","https://openalex.org/W3127927415","https://openalex.org/W3214554553","https://openalex.org/W4319341370","https://openalex.org/W4377231569","https://openalex.org/W4384916898","https://openalex.org/W4385439679","https://openalex.org/W4388486527","https://openalex.org/W4390967218","https://openalex.org/W4391216147","https://openalex.org/W4393065874","https://openalex.org/W4396779970","https://openalex.org/W4400943062","https://openalex.org/W4402082691","https://openalex.org/W4402484179","https://openalex.org/W4403561496","https://openalex.org/W4404635382","https://openalex.org/W4404996543","https://openalex.org/W4408160073","https://openalex.org/W4412152448","https://openalex.org/W4413682696","https://openalex.org/W4415178556","https://openalex.org/W4415792109","https://openalex.org/W4416069063","https://openalex.org/W4416099127","https://openalex.org/W4416345316","https://openalex.org/W4416412519","https://openalex.org/W4416418883","https://openalex.org/W4417259841"],"related_works":[],"abstract_inverted_index":{"Hypergraph":[0],"Neural":[1],"Networks":[2],"(HGNNs)":[3],"have":[4],"become":[5],"an":[6,97],"important":[7],"tool":[8],"for":[9,113],"processing":[10],"complex":[11],"structured":[12],"data":[13],"due":[14],"to":[15,18,90,133,158,189],"their":[16],"ability":[17],"model":[19],"higher-order":[20],"associative":[21],"relationships.":[22],"However,":[23],"the":[24,52,83,87,135,140,145,160,169,174,201],"inherent":[25],"adversarial":[26],"vulnerabilities":[27],"of":[28,55,177,219],"HGNNs":[29,67,114],"may":[30],"raise":[31],"serious":[32],"security":[33],"risks.":[34],"The":[35,123],"associated":[36],"risks":[37],"are":[38,47,142],"far":[39],"more":[40],"pronounced":[41],"in":[42,96,217],"strong":[43,91],"target":[44,60,75,92,137,190],"attacks,":[45,76],"which":[46],"highly":[48],"targeted":[49],"and":[50,77,119,129,166,180,200,211],"demand":[51],"accurate":[53],"misclassification":[54,184],"source-class":[56],"nodes":[57,141,165,188],"into":[58],"predefined":[59],"classes.":[61,191],"Current":[62],"research":[63,88,103],"on":[64,70,116,196],"attacks":[65,72,79,93],"against":[66],"mostly":[68],"focuses":[69],"untargeted":[71],"or":[73],"common":[74],"lacks":[78],"that":[80,205],"precisely":[81],"control":[82],"attack":[84,209],"class.":[85,138],"Therefore,":[86],"related":[89],"is":[94,156],"still":[95],"undeveloped":[98],"state.":[99],"To":[100],"fill":[101],"this":[102,105],"gap,":[104],"paper":[106],"proposes":[107],"a":[108],"Strong":[109],"Target":[110],"Attack":[111],"framework":[112,124],"based":[115],"Label":[117],"poisoning":[118],"Structure":[120],"modification":[121,171],"(STALS).":[122],"first":[125],"uses":[126],"feature":[127],"similarity":[128],"hypergraph":[130],"structure":[131,170],"adaptability":[132],"select":[134],"optimal":[136],"Subsequently,":[139],"label-poisoned":[143],"under":[144],"label":[146],"change":[147],"budget":[148],"constraint.":[149],"A":[150],"gradient-guided":[151],"greedy":[152],"hyperedge":[153],"reconstruction":[154],"strategy":[155],"used":[157],"optimize":[159],"association":[161],"relationship":[162],"between":[163],"poisoned":[164],"hyperedges":[167],"within":[168],"budget,":[172],"maximize":[173],"propagation":[175],"efficiency":[176],"mislabeled":[178],"information,":[179],"achieve":[181],"stable":[182],"directed":[183],"from":[185],"source":[186],"class":[187],"We":[192],"conducted":[193],"extensive":[194],"experiments":[195],"four":[197],"mainstream":[198],"datasets,":[199],"experimental":[202],"results":[203],"show":[204],"STALS":[206],"achieves":[207],"excellent":[208],"performance":[210],"significantly":[212],"outperforms":[213],"existing":[214],"baseline":[215],"methods":[216],"terms":[218],"success":[220],"classification":[221],"rate.":[222]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-03-10T00:00:00"}
