{"id":"https://openalex.org/W7170060201","doi":"https://doi.org/10.48550/arxiv.2607.18869","title":"Tracing the Shadows: Automatic Tracking and Analysis of Crypto Money Laundering via Transaction Semantic Analysis","display_name":"Tracing the Shadows: Automatic Tracking and Analysis of Crypto Money Laundering via Transaction Semantic Analysis","publication_year":2026,"publication_date":"2026-07-21","ids":{"openalex":"https://openalex.org/W7170060201","doi":"https://doi.org/10.48550/arxiv.2607.18869"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.18869","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.18869","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.18869","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113485823","display_name":"H. Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143410018","display_name":"Haijun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Haijun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048520197","display_name":"Shiteng Li","orcid":"https://orcid.org/0009-0001-5110-1931"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Shangwang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143430726","display_name":"Yin Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143398043","display_name":"Ming Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Ming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143415537","display_name":"Ting Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Ting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090665711","display_name":"Xiaoman Luo","orcid":"https://orcid.org/0000-0001-9987-1399"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Xiapu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11838","display_name":"Crime, Illicit Activities, and Governance","score":0.7723000049591064,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11838","display_name":"Crime, Illicit Activities, and Governance","score":0.7723000049591064,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.1485999971628189,"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/T12519","display_name":"Cybercrime and Law Enforcement Studies","score":0.015699999406933784,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/money-laundering","display_name":"Money laundering","score":0.7944999933242798},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.6523000001907349},{"id":"https://openalex.org/keywords/cryptocurrency","display_name":"Cryptocurrency","score":0.5644999742507935},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5631999969482422},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.5327000021934509},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.44850000739097595},{"id":"https://openalex.org/keywords/security-analysis","display_name":"Security analysis","score":0.41679999232292175},{"id":"https://openalex.org/keywords/semantic-analysis","display_name":"Semantic analysis (machine learning)","score":0.3601999878883362},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.35580000281333923}],"concepts":[{"id":"https://openalex.org/C2780005421","wikidata":"https://www.wikidata.org/wiki/Q151900","display_name":"Money laundering","level":2,"score":0.7944999933242798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7703999876976013},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.6528000235557556},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.6523000001907349},{"id":"https://openalex.org/C180706569","wikidata":"https://www.wikidata.org/wiki/Q13479982","display_name":"Cryptocurrency","level":2,"score":0.5644999742507935},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5631999969482422},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.5327000021934509},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.44850000739097595},{"id":"https://openalex.org/C38369872","wikidata":"https://www.wikidata.org/wiki/Q7445009","display_name":"Security analysis","level":2,"score":0.41679999232292175},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.3601999878883362},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C2781317605","wikidata":"https://www.wikidata.org/wiki/Q7832483","display_name":"Traffic analysis","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C6881194","wikidata":"https://www.wikidata.org/wiki/Q7449091","display_name":"Semantic technology","level":4,"score":0.33489999175071716},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C127722929","wikidata":"https://www.wikidata.org/wiki/Q7833714","display_name":"Transaction data","level":3,"score":0.3296000063419342},{"id":"https://openalex.org/C164516710","wikidata":"https://www.wikidata.org/wiki/Q1166072","display_name":"Financial transaction","level":3,"score":0.3206000030040741},{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.31130000948905945},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2782999873161316},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2669999897480011}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.18869","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.18869","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.18869","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.18869","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8135852217674255}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,29,51,74,174,189,221],"rapid":[2],"advancement":[3],"of":[4,31,54,77,191,215,225,232],"decentralized":[5],"finance":[6],"(DeFi),":[7],"security":[8],"incidents":[9],"related":[10],"to":[11,23,48,72,131,163],"cryptocurrency":[12],"have":[13],"become":[14],"increasingly":[15],"prevalent.":[16],"After":[17],"such":[18],"incidents,":[19],"attackers":[20],"typically":[21],"attempt":[22],"rapidly":[24],"move":[25],"stolen":[26],"assets,":[27],"concealing":[28],"origin":[30],"illicit":[32,94,199,209],"funds":[33],"and":[34,111,159,217,227,229,234,238],"ultimately":[35],"converting":[36],"them":[37],"into":[38,140,181],"fiat":[39],"currency.":[40],"However,":[41],"existing":[42],"anti-money":[43],"laundering":[44,113,149,196],"(AML)":[45],"methods":[46],"struggle":[47],"cope":[49],"with":[50,124,212],"semantic":[52,103,142],"complexity":[53],"DeFi":[55,107,134,183],"transactions.":[56,78],"They":[57],"either":[58],"rely":[59],"heavily":[60],"on":[61,105,173,193,236],"low-level":[62],"token":[63],"transfers,":[64],"or":[65],"perform":[66],"protocol-agnostic":[67],"money":[68],"flow":[69],"analysis,":[70],"failing":[71],"capture":[73],"high-level":[75,141],"intent":[76,150],"In":[79],"this":[80],"paper,":[81],"we":[82],"propose":[83],"AMLGuard,":[84],"a":[85,116,182],"semantic-aware":[86],"AML":[87],"framework":[88],"for":[89,145],"account-based":[90],"blockchains.":[91],"AMLGuard":[92,119,155,177,192,206],"tracks":[93],"fund":[95],"flows":[96],"from":[97],"known":[98],"malicious":[99],"addresses":[100],"by":[101],"performing":[102],"analysis":[104,123],"complex":[106,117],"transactions,":[108],"enabling":[109,167],"accurate":[110],"continuous":[112],"tracking.":[114],"Given":[115],"transaction,":[118],"combines":[120],"static":[121],"rule-based":[122],"retrieval-augmented":[125],"large":[126],"language":[127],"model":[128],"(LLM)":[129],"reasoning":[130],"infer":[132],"implicit":[133],"semantics,":[135,166,176],"transforming":[136],"raw":[137],"transaction":[138,157,180],"data":[139],"representations.":[143],"Furthermore,":[144],"cross-chain":[146,165,239],"transactions":[147],"where":[148],"is":[151],"not":[152],"explicitly":[153],"exposed,":[154],"parses":[156],"parameters":[158],"performs":[160],"argument":[161],"parsing":[162],"recover":[164],"seamless":[168],"tracking":[169],"across":[170],"ledgers.":[171],"Based":[172],"inferred":[175],"abstracts":[178],"each":[179],"Semantic":[184],"Unit":[185],"(DSU).":[186],"We":[187],"evaluate":[188],"effectiveness":[190],"82":[194],"real-world":[195],"cases,":[197],"involving":[198],"assets":[200],"worth":[201],"over":[202],"$1":[203],"billion.":[204],"Specifically,":[205],"reconstructs":[207],"compact":[208],"fund-flow":[210],"topologies":[211],"destination":[213,230],"precision":[214],"94.4%":[216],"87.6%,":[218],"while":[219],"achieving":[220],"highest":[222],"address":[223],"recall":[224,231],"98.4%":[226],"95.8%":[228],"94.1%":[233],"93.8%":[235],"single-chain":[237],"datasets.":[240]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-23T00:00:00"}