{"id":"https://openalex.org/W4401720526","doi":"https://doi.org/10.1109/icbc59979.2024.10634350","title":"Leveraging Machine Learning For Multichain DeFi Fraud Detection","display_name":"Leveraging Machine Learning For Multichain DeFi Fraud Detection","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4401720526","doi":"https://doi.org/10.1109/icbc59979.2024.10634350"},"language":"en","primary_location":{"id":"doi:10.1109/icbc59979.2024.10634350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbc59979.2024.10634350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","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/A5040196236","display_name":"Georgios Palaiokrassas","orcid":"https://orcid.org/0000-0001-8573-1416"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Georgios Palaiokrassas","raw_affiliation_strings":["Yale University,Department of Electrical Engineering,New Haven,CT,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University,Department of Electrical Engineering,New Haven,CT,USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092188028","display_name":"Sandro Scherrers","orcid":null},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sandro Scherrers","raw_affiliation_strings":["Yale University,Yale Institute for Network Science,New Haven,CT,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University,Yale Institute for Network Science,New Haven,CT,USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053398628","display_name":"Iason Ofeidis","orcid":"https://orcid.org/0000-0001-8206-8321"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Iason Ofeidis","raw_affiliation_strings":["Yale University,Department of Electrical Engineering,New Haven,CT,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University,Department of Electrical Engineering,New Haven,CT,USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014892027","display_name":"Leandros Tassiulas","orcid":"https://orcid.org/0000-0003-0932-774X"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leandros Tassiulas","raw_affiliation_strings":["Yale University,Department of Electrical Engineering,New Haven,CT,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University,Department of Electrical Engineering,New Haven,CT,USA","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I32971472"],"apc_list":null,"apc_paid":null,"fwci":3.583,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.93672806,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"678","last_page":"680"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9962000250816345,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9962000250816345,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9376000165939331,"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/computer-science","display_name":"Computer science","score":0.739403486251831},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4993908405303955},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4498540163040161}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.739403486251831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4993908405303955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4498540163040161}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icbc59979.2024.10634350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbc59979.2024.10634350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1560107318","https://openalex.org/W2056168656","https://openalex.org/W2775379762","https://openalex.org/W2914651641","https://openalex.org/W3033451189","https://openalex.org/W3043060424","https://openalex.org/W3093496714","https://openalex.org/W3126663487","https://openalex.org/W3151748982","https://openalex.org/W3179573039","https://openalex.org/W3201534837","https://openalex.org/W3203029673","https://openalex.org/W3205419167","https://openalex.org/W3210902158","https://openalex.org/W4211068006","https://openalex.org/W4212941551","https://openalex.org/W4213135868","https://openalex.org/W4221166476","https://openalex.org/W4224884870","https://openalex.org/W4248175462","https://openalex.org/W4285151409","https://openalex.org/W4288072839","https://openalex.org/W4288276219","https://openalex.org/W4304208336","https://openalex.org/W4304208374","https://openalex.org/W4312660944","https://openalex.org/W4312961006","https://openalex.org/W4322749589","https://openalex.org/W4380886801","https://openalex.org/W4393284065","https://openalex.org/W6766612752","https://openalex.org/W6793285265","https://openalex.org/W6809618313"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Smart":[0],"contracts":[1],"across":[2],"Blockchains":[3],"provide":[4],"an":[5,48,57,74],"ecosystem":[6],"of":[7,31,45,50,64,80,129],"decentralized":[8],"finance":[9],"(DeFi),":[10],"with":[11,24,77,95,121],"a":[12,62,90,105,111],"total":[13],"locked":[14],"value":[15],"which":[16],"had":[17],"exceeded":[18],"160B":[19],"USD.":[20],"While":[21],"DeFi":[22,86,122],"comes":[23],"high":[25,51],"rewards,":[26],"it":[27,70],"also":[28],"carries":[29],"plenty":[30],"risks.":[32],"Many":[33],"financial":[34],"crimes":[35],"have":[36],"occurred":[37],"over":[38,73],"the":[39,42,78,81,127,135],"years":[40],"making":[41],"early":[43],"detection":[44],"malicious":[46],"activity":[47],"issue":[49],"priority.":[52],"The":[53],"proposed":[54],"framework":[55],"introduces":[56],"effective":[58],"method":[59],"for":[60,116],"extracting":[61],"set":[63],"features":[65],"from":[66],"different":[67],"chains,":[68],"and":[69,110,123],"is":[71],"evaluated":[72],"extensive":[75],"dataset":[76,92],"transactions":[79],"23":[82],"most":[83],"widely":[84],"used":[85],"protocols":[87],"based":[88],"on":[89],"novel":[91,130],"in":[93],"collaboration":[94],"Covalent.":[96],"Different":[97],"Machine":[98],"Learning":[99],"methods":[100],"were":[101],"employed,":[102],"such":[103],"as":[104],"Deep":[106],"Neural":[107],"Network,":[108],"XGBoost,":[109],"fine-tuned":[112],"Large":[113],"Language":[114],"Model":[115],"identifying":[117],"fraud":[118],"accounts":[119],"interacting":[120],"we":[124],"demonstrate":[125],"that":[126],"introduction":[128],"DeFi-related":[131],"features,":[132],"significantly":[133],"improves":[134],"evaluation":[136],"results.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
