{"id":"https://openalex.org/W7125225803","doi":"https://doi.org/10.1109/cloudcom67567.2025.11331465","title":"Airdrop Hunter Detection via PageRank-Augmented Multimodal Graph Neural Networks","display_name":"Airdrop Hunter Detection via PageRank-Augmented Multimodal Graph Neural Networks","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W7125225803","doi":"https://doi.org/10.1109/cloudcom67567.2025.11331465"},"language":null,"primary_location":{"id":"doi:10.1109/cloudcom67567.2025.11331465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloudcom67567.2025.11331465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 lEEE International Conference on Cloud Computing Technology and Science (CloudCom)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5123479244","display_name":"Jiajie Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiajie Shi","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123469764","display_name":"Yuyang Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang Qin","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032620407","display_name":"Hengming Dai","orcid":"https://orcid.org/0000-0002-8206-5902"},"institutions":[{"id":"https://openalex.org/I4210131885","display_name":"Yunnan Institute of Environmental Sciences","ror":"https://ror.org/03krx0543","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210131885"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengming Dai","raw_affiliation_strings":["Institute of International Rivers and Eco-Security, Yunnan University,Kunming,China"],"affiliations":[{"raw_affiliation_string":"Institute of International Rivers and Eco-Security, Yunnan University,Kunming,China","institution_ids":["https://openalex.org/I4210131885"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123465266","display_name":"Xiaoyi Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyi Fan","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China","institution_ids":["https://openalex.org/I4388482657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068512767","display_name":"Haihan Duan","orcid":"https://orcid.org/0000-0001-6438-3790"},"institutions":[{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haihan Duan","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University,Guangdong,China","institution_ids":["https://openalex.org/I4388482657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5123479244"],"corresponding_institution_ids":["https://openalex.org/I4388482657"],"apc_list":null,"apc_paid":null,"fwci":1.3864,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.86976148,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.11900000274181366,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.11900000274181366,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10742","display_name":"Peer-to-Peer Network Technologies","score":0.11869999766349792,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.11710000038146973,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7688000202178955},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6093000173568726},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5382000207901001},{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.49410000443458557},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.4925999939441681},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43880000710487366},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.41499999165534973},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3896999955177307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7961000204086304},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7688000202178955},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6093000173568726},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5382000207901001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.510200023651123},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.4925999939441681},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43880000710487366},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.41499999165534973},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.374099999666214},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.30219998955726624},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C72108876","wikidata":"https://www.wikidata.org/wiki/Q844565","display_name":"Transaction processing","level":3,"score":0.29989999532699585},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2928999960422516},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.26919999718666077},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.26109999418258667}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cloudcom67567.2025.11331465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloudcom67567.2025.11331465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 lEEE International Conference on Cloud Computing Technology and Science (CloudCom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5235010981559753}],"awards":[{"id":"https://openalex.org/G8465124245","display_name":null,"funder_award_id":"62576213","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1520914943","https://openalex.org/W2051381393","https://openalex.org/W2154851992","https://openalex.org/W2962756421","https://openalex.org/W2963341956","https://openalex.org/W3160022184","https://openalex.org/W4231449374","https://openalex.org/W4239510810","https://openalex.org/W4288073028","https://openalex.org/W4327670850","https://openalex.org/W4388196927","https://openalex.org/W4396735717","https://openalex.org/W4405491909","https://openalex.org/W4405949023","https://openalex.org/W4408182971","https://openalex.org/W4409233268"],"related_works":[],"abstract_inverted_index":{"Airdrops":[0],"are":[1,20,150],"a":[2,59,129],"widely":[3],"used":[4],"mechanism":[5],"in":[6,65,107,172],"Web3":[7],"ecosystems":[8],"to":[9,53,96],"incentivize":[10],"early":[11],"users":[12],"by":[13,23,82],"distributing":[14],"governance":[15],"tokens.":[16],"However,":[17],"these":[18],"mechanisms":[19],"increasingly":[21],"targeted":[22],"airdrop":[24],"hunters\u2014malicious":[25],"actors":[26],"who":[27],"exploit":[28],"token":[29],"distribution":[30],"systems":[31],"through":[32],"address":[33],"farming,":[34],"automated":[35],"scripts,":[36],"and":[37,49,124,165],"behavioral":[38],"camouflage.":[39],"While":[40],"prior":[41],"work":[42],"such":[43,55],"as":[44,87],"ARTEMIS":[45,81],"leverages":[46],"multimodal":[47],"features":[48,137],"local":[50],"transaction":[51,67],"patterns":[52],"detect":[54],"behavior,":[56],"it":[57],"lacks":[58],"global":[60,85],"understanding":[61],"of":[62,162,169],"wallet":[63],"influence":[64,106],"the":[66,80,94,108,121,148,160,166],"graph.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72],"propose":[73],"an":[74,88],"enhanced":[75],"detection":[76,174],"framework":[77],"that":[78,134,147],"augments":[79],"incorporating":[83],"PageRank-based":[84],"centrality":[86],"additional":[89],"structural":[90,163],"feature.":[91],"This":[92],"allows":[93],"model":[95],"better":[97],"distinguish":[98],"superficially":[99],"active":[100],"wallets":[101],"from":[102,120],"those":[103],"with":[104,153],"broader":[105],"network.":[109],"We":[110],"evaluate":[111],"our":[112],"method":[113],"on":[114],"real-world":[115],"Non-Fungible":[116],"Token":[117],"(NFT)":[118],"data":[119],"Blur":[122],"marketplace":[123],"achieve":[125,140],"state-of-the-art":[126],"performance.":[127],"Furthermore,":[128],"feature":[130],"substitution":[131],"experiment":[132],"reveals":[133],"simple":[135],"degree-based":[136],"alone":[138],"can":[139],"near-perfect":[141],"performance,":[142],"even":[143],"outperforming":[144],"PageRank,":[145],"suggesting":[146],"labels":[149],"strongly":[151],"coupled":[152],"topological":[154],"properties.":[155],"These":[156],"findings":[157],"highlight":[158],"both":[159],"effectiveness":[161],"augmentation":[164],"potential":[167],"risks":[168],"shortcut":[170],"learning":[171],"graph-based":[173],"systems.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2026-01-22T00:00:00"}