{"id":"https://openalex.org/W4412877112","doi":"https://doi.org/10.1145/3711896.3737184","title":"A Fraudulent Blind Shipment Detection Framework in Logistics","display_name":"A Fraudulent Blind Shipment Detection Framework in Logistics","publication_year":2025,"publication_date":"2025-08-03","ids":{"openalex":"https://openalex.org/W4412877112","doi":"https://doi.org/10.1145/3711896.3737184"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3737184","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737184","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737184","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737184","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hongyu Lin","orcid":"https://orcid.org/0009-0002-1680-1251"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hongyu Lin","raw_affiliation_strings":["HKUST (GZ), Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-1680-1251","affiliations":[{"raw_affiliation_string":"HKUST (GZ), Guangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014020768","display_name":"Shuxin Zhong","orcid":"https://orcid.org/0009-0006-1758-2870"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuxin Zhong","raw_affiliation_strings":["HKUST (GZ), Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0006-1758-2870","affiliations":[{"raw_affiliation_string":"HKUST (GZ), Guangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yan Fang","orcid":"https://orcid.org/0009-0008-3325-6973"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Fang","raw_affiliation_strings":["USTC, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0008-3325-6973","affiliations":[{"raw_affiliation_string":"USTC, Hefei, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077830473","display_name":"Zhiqing Hong","orcid":"https://orcid.org/0000-0003-3682-4290"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiqing Hong","raw_affiliation_strings":["Rutgers University, Piscataway, USA"],"raw_orcid":"https://orcid.org/0000-0003-3682-4290","affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078574526","display_name":"Wenjun Lyu","orcid":"https://orcid.org/0000-0002-7885-3105"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenjun Lyu","raw_affiliation_strings":["Rutgers University, Piscataway, USA"],"raw_orcid":"https://orcid.org/0000-0002-7885-3105","affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000977930","display_name":"Qipeng Xie","orcid":"https://orcid.org/0000-0002-5500-0249"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qipeng Xie","raw_affiliation_strings":["HKUST (GZ), Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5500-0249","affiliations":[{"raw_affiliation_string":"HKUST (GZ), Guangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101710780","display_name":"Haotian Wang","orcid":"https://orcid.org/0000-0001-9783-6389"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haotian Wang","raw_affiliation_strings":["JD Logistic, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9783-6389","affiliations":[{"raw_affiliation_string":"JD Logistic, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364381","display_name":"Lu Wang","orcid":"https://orcid.org/0000-0001-6345-3873"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Wang","raw_affiliation_strings":["Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6345-3873","affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001188748","display_name":"Kaishun Wu","orcid":"https://orcid.org/0000-0003-2216-0737"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaishun Wu","raw_affiliation_strings":["HKUST (GZ), Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2216-0737","affiliations":[{"raw_affiliation_string":"HKUST (GZ), Guangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1733,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.89625285,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4590","last_page":"4598"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9972000122070312,"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":0.9972000122070312,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9563000202178955,"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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9204999804496765,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5116636753082275},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.4148208200931549},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3962712287902832}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5116636753082275},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.4148208200931549},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3962712287902832}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711896.3737184","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737184","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737184","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3711896.3737184","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737184","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737184","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1170000390","display_name":null,"funder_award_id":"U2001207","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3701253004","display_name":null,"funder_award_id":"62372307","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3965030583","display_name":null,"funder_award_id":"2023KCXTD042","funder_id":"https://openalex.org/F4320326279","funder_display_name":"Department of Education of Guangdong Province"},{"id":"https://openalex.org/G5456191044","display_name":null,"funder_award_id":"U2001207","funder_id":"https://openalex.org/F4320326279","funder_display_name":"Department of Education of Guangdong Province"},{"id":"https://openalex.org/G8000406786","display_name":null,"funder_award_id":"62472366","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8484321584","display_name":null,"funder_award_id":"ZDSYS20190902092853047","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8982764754","display_name":null,"funder_award_id":"D25008","funder_id":"https://openalex.org/F4320336698","funder_display_name":"Overseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center)"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326279","display_name":"Department of Education of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320336698","display_name":"Overseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center)","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412877112.pdf","grobid_xml":"https://content.openalex.org/works/W4412877112.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2077949207","https://openalex.org/W2101057136","https://openalex.org/W2350778671","https://openalex.org/W3153858161","https://openalex.org/W4220721362","https://openalex.org/W4317767731","https://openalex.org/W4367046762","https://openalex.org/W4382469817","https://openalex.org/W4385568054","https://openalex.org/W4388867283","https://openalex.org/W4392367398","https://openalex.org/W4393161202","https://openalex.org/W4396523412","https://openalex.org/W4396735669","https://openalex.org/W4396832790","https://openalex.org/W4396843600","https://openalex.org/W4401856724","https://openalex.org/W4401857640","https://openalex.org/W4401857656","https://openalex.org/W4401863317","https://openalex.org/W4401863463","https://openalex.org/W4401863513","https://openalex.org/W4401863589","https://openalex.org/W4401863775","https://openalex.org/W4401863964","https://openalex.org/W4401864369","https://openalex.org/W6600238479","https://openalex.org/W6602430550","https://openalex.org/W6689144392"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"An":[0],"emerging":[1,57],"type":[2],"of":[3,20,90,179,184],"fraud":[4,58,84,91,106,180],"involves":[5],"malicious":[6],"senders":[7],"exploiting":[8],"the":[9,41,177],"blind":[10],"shipment":[11,116],"and":[12,35,62,103,155,182,203],"cash-on-delivery":[13],"(COD)":[14],"mechanisms":[15],"by":[16,124],"dispatching":[17],"large":[18,125],"volumes":[19],"unsolicited,":[21],"low-cost":[22],"parcels.":[23],"If":[24],"unsuspecting":[25],"receivers":[26],"accept":[27],"these":[28],"parcels,":[29],"they":[30],"pay":[31],"for":[32,83,119],"both":[33],"shipping":[34,43],"goods;":[36],"otherwise,":[37],"logistics":[38],"providers":[39],"bear":[40],"round-trip":[42],"costs.":[44],"Existing":[45],"detection":[46,117],"techniques,":[47],"which":[48],"rely":[49],"on":[50,192],"extensive":[51],"labeled":[52],"cases,":[53],"struggle":[54],"with":[55,233],"this":[56],"because":[59],"receivers'":[60,77],"unawareness":[61],"low":[63],"transaction":[64],"values":[65],"discourage":[66],"complaints,":[67,78],"resulting":[68],"in":[69,217,224],"few":[70],"confirmed":[71],"cases.":[72],"Therefore,":[73],"we":[74,111],"propose":[75],"leveraging":[76],"though":[79],"not":[80],"initially":[81],"collected":[82,197],"detection,":[85],"to":[86,137,146,163,175],"uncover":[87],"subtle":[88],"indicators":[89],"patterns,":[92,186],"while":[93],"addressing":[94,153,169,187],"three":[95,132],"challenges:":[96],"(C1)":[97],"noise-rich":[98],"dialogues(C2)":[99],"data":[100],"privacy":[101],"concerns,":[102],"(C3)":[104],"ever-evolving":[105],"patterns.":[107],"To":[108],"address":[109],"them,":[110],"design":[112],"BLOFF,":[113],"a":[114,159,164,214,234],"Blind":[115],"Framework":[118],"LO":[120],"gistics":[121],"Fraud":[122],"powered":[123],"language":[126],"models":[127],"(LLMs).":[128],"Specifically,":[129],"BLOFF":[130,191,209,227],"includes":[131],"components:":[133],"i)":[134],"Sensitivity":[135],"Anonymization":[136],"protect":[138],"sensitive":[139],"user":[140],"information;":[141],"ii)":[142,171],"Dialogue":[143],"Profile":[144],"Distillation":[145],"transform":[147],"informal":[148],"dialogues":[149],"into":[150],"structured":[151],"representation,":[152],"C1,":[154],"distill":[156],"knowledge":[157],"from":[158,198],"teacher":[160],"LLM":[161,167],"(GPT-4o)":[162],"lightweight":[165],"student":[166],"(ChatGLM4-9B),":[168],"C2;":[170],"Multi-faceted":[172],"Context":[173],"Augmentation":[174],"enhance":[176],"interpretation":[178],"signatures":[181],"adaptation":[183],"evolving":[185],"C3.":[188],"We":[189],"evaluate":[190],"about":[193],"56,000":[194],"complaints":[195],"records":[196],"JD":[199],"Logistics":[200],"between":[201],"January":[202],"November":[204],"2024.":[205],"Results":[206],"show":[207],"that":[208],"outperforms":[210],"state-of-the-art":[211],"methods,":[212],"achieving":[213],"10.19%":[215],"improvement":[216],"precision.":[218,236],"Furthermore,":[219],"during":[220],"its":[221],"real-world":[222],"deployment":[223],"December":[225],"2024,":[226],"identified":[228],"over":[229],"90":[230],"fraudulent":[231],"parcels":[232],"91.4%":[235]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
