[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124833-en":3,"doc-seo-124833-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124833,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Research & Report","Prediction of Illicit Transactions on the Bitcoin Blockchain Using Machine Learning - Undergraduate Research Scholars Thesis","Prediction of illicit transactions on the Bitcoin blockchain using machine learning addresses how decentralized ledgers create opportunities for money laundering through multi-wallet movement and exchange cash-out. The thesis leverages the Elliptic data set, mapping Bitcoin transactions to entities labeled licit or illicit, to support anti-money laundering analysis. Graph visualization is used to explore patterns among licit versus illicit nodes, and multiple binary classification models evaluate predictive performance and network structure insights.","PREDICTION OF ILLICIT TRANSACTIONS ON THE BITCOIN BLOCKCHAIN  \nUSING MACHINE LEARNING  \nAn Undergraduate Research Scholars Thesis  \nby  \nJACK SEBASTIAN  \nSubmitted to the LAUNCH: Undergraduate Research office at Texas A&M University  \nin partial fulfillment of the requirements for the designation as an  \nUNDERGRADUATE RESEARCH SCHOLAR  \nApproved by  \nFaculty Research Advisor: Dr. James Caverlee  \nMay 2023  \nMajors: Computer Science  \nApplied Mathematics  \nCopyright © 2023 . Jack Sebastian.  \nRESEARCH COMPLIANCE CERTIFICATION  \nResearch activities involving the use of human subjects, vertebrate animals, and/or biohazards must be reviewed and approved by the appropriate Texas A&M University regulatory research committee (i.e., IRB, IACUC, IBC) before the activity can commence. This requirement applies to activities conducted at Texas A&M and to activities conducted at non-Texas A&M facilities or institutions. In both cases, students are responsible for working with the relevant Texas A&M research compliance program to ensure and document that all Texas A&M compliance obligations are met before the study begins.  \nI, Jack Sebastian, certify that all research compliance requirements related to this Undergraduate Research Scholars thesis have been addressed with my Faculty Research Advisor prior to the collection of any data used in this final thesis submission.  \nThis project did not require approval from the Texas A&M University Research Compliance & Biosafety office.  \nTABLE OF CONTENTS  \nPage  \nABSTRACT ......................................................................................... 1  \nACKNOWLEDGMENTS .......................................................................... 3  \nNOMENCLATURE ................................................................................. 4  \n1. INTRODUCTION ............................................................................... 5  \n1.1 Cryptocurrency and blockchain .......................................................... 5  \n1.2 Money Laundering ........................................................................ 6  \n1.3 Elliptic Data Set ........................................................................... 8  \n1.4 Future plans and goals .................................................................... 8  \n2. METHODS ...................................................................................... 9  \n2.1 Data Preprocessing ........................................................................ 9  \n2.2 Binary Classification ...................................................................... 10  \n2.3 Evaluation Metrics ........................................................................ 23  \n3. RESULTS ........................................................................................ 26  \n4. CONCLUSION .................................................................................. 28  \nREFERENCES ...................................................................................... 30  \nABSTRACT  \nPrediction of Illicit Transactions on the Bitcoin Blockchain Using Machine Learning  \nJack Sebastian  \nDepartment of Computer Science and Engineering  \nTexas A&M University  \nFaculty Research Advisor: Dr. James Caverlee  \nDepartment of Computer Science and Engineering  \nTexas A&M University  \nWith the emergence of cryptocurrencies and blockchain technology, the paradigm of the structure of data storing and distribution has completely changed. And while the central goal of Bitcoin’s 2008 whitepaper was to create internet-based peer-to-peer money without a central third party, there are some unforeseen issues that come with having a completely decentralized ledger. Money laundering is possible by moving illicit funds through hundreds of wallets before depositing the funds and cashing out with a crypto exchange. And with these methods of money laundering becoming more advanced over the decades, the advent of cryptocurrency means a new venue for crimi","cbCaiaE2QAlOQshE","https://ap.wps.com/l/cbCaiaE2QAlOQshE","pdf",371626,1,33,"English","en",105,"# Abstract\n# Acknowledgments\n# Nomenclature\n# Introduction\n## Cryptocurrency and blockchain\n## Money Laundering\n## Elliptic Data Set\n## Future plans and goals\n# Methods\n## Data Preprocessing\n## Binary Classification\n## Evaluation Metrics\n# Results\n# Conclusion\n# References","[{\"question\":\"What problem does the thesis address on the Bitcoin blockchain?\",\"answer\":\"It focuses on predicting illicit transactions and supporting anti-money-laundering efforts despite how decentralized systems can enable laundering through many wallets and exchanges.\"},{\"question\":\"Which dataset is used for training and evaluation?\",\"answer\":\"The Elliptic data set is used, mapping Bitcoin transactions to entities categorized as licit or illicit and containing over 200,000 nodes and 230,000 edges.\"},{\"question\":\"Which machine learning models are evaluated for binary classification?\",\"answer\":\"Logistic Regression, K-Nearest Neighbours, Decision Trees, Multilayer Perceptron, Random Forest, and Graph Attention Networks are applied to the Elliptic data set.\"}]","Prediction of Illicit Transactions on the Bitcoin Blockchain Using Machine Learning - Undergraduate Research Scholars Thesis | PDF",1785894892,83,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"prediction-of-illicit-transactions-on-the-bitcoin-blockchain-using-machine-learning-undergraduate-research-scholars-thesis","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/prediction-of-illicit-transactions-on-the-bitcoin-blockchain-using-machine-learning-undergraduate-research-scholars-thesis/124833/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the thesis address on the Bitcoin blockchain?","Question",{"text":75,"@type":76},"It focuses on predicting illicit transactions and supporting anti-money-laundering efforts despite how decentralized systems can enable laundering through many wallets and exchanges.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which dataset is used for training and evaluation?",{"text":80,"@type":76},"The Elliptic data set is used, mapping Bitcoin transactions to entities categorized as licit or illicit and containing over 200,000 nodes and 230,000 edges.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning models are evaluated for binary classification?",{"text":84,"@type":76},"Logistic Regression, K-Nearest Neighbours, Decision Trees, Multilayer Perceptron, Random Forest, and Graph Attention Networks are applied to the Elliptic data set.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]