[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121186-en":3,"doc-seo-121186-105":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":20,"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},121186,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Enhancing Smart Contract Security - A Machine Learning Framework Using Natural Language Processing and Unsupervised Techniques","This thesis explores smart contract security through natural language processing and unsupervised machine learning. Reports from Code4Arena are analyzed with k-means and Latent Dirichlet Allocation to extract patterns in smart contract usage, vulnerabilities, and potential attack methods. The research highlights emerging trends in security threats and demonstrates how machine learning can support vulnerability detection. A framework is proposed to improve security using real-world case studies and cross-platform blockchain data, validated with a pipeline that evaluates contracts and assigns a severity score.","M Data S  \nMaster Degree Program incience and Advanced Analytics  \nEnhancing Smart Contract Security: A Machine Learning Framework Using Natural Language Processing and Unsupervised Techniques  \nMacovei Andrei  \nMaster Thesis  \nNOVA Information Management School Instituto Superior de Estatística e Gestão de Informação  \nUniversidade Nova de Lisboa  \nNOVA Information Management School Instituto Superior de Estatística e Gestão de Informação  \nUniversidade Nova de Lisboa  \nEnhancing Smart Contract Security: A Machine Learning Framework Using Natural Language Processing and Unsupervised Techniques  \nby  \nMacovei Andrei  \nMaster Thesis presented as partial requirement for obtaining the Master’s degree in Data Science and Advanced Analytics, with a specialization in Business Analytics  \nSupervised by  \nIan James Scott, PhD, NOVA Information Management School  \nJune, 2024  \nSTATEMENT OF INTEGRITY  \nI hereby declare having conducted this academic work with integrity. I confirm that I have not used plagiarism or any form of undue use of information or falsification of results along the process leading to its elaboration. I further declare that I have fully acknowledged the Rules of Conduct and Code of Honor from the NOVA Information Management School.  \n[Lisbon, July 12,2024]  \nDEDICATION  \nI want to dedicate this thesis to my family for allowing me to pursue this master's degree here and to my fiancée, Atenea, who has supported me.  \nACKNOWLEDGEMENTS  \nI would like to express my gratitude to Professor Ian James Scott for trusting me with the chance to write this thesis under his guidance. Working with the professor was a pleasure, and his advice was useful in finishing my master's thesis.  \nABSTRACT  \nThis thesis explored smart contract security using natural language processing and unsupervised machine learning techniques. By analyzing reports from Code4Arena and applying k-means and Latent Dirichlet Allocation, I aimed to identify trends in smart contract usage, vulnerabilities, and potential attack methods. My analysis yielded valuable insights for blockchain developers and cybersecurity professionals. The research identified trends in smart contract security threats and the potential of using machine learning for vulnerability detection. I propose a framework to enhance smart contract security based on real-world case studies and data from various blockchain platforms. This framework, informed by the identified trends, can contribute to building more secure blockchain ecosystems. The results indicate that the developed pipeline can efficiently evaluate various smart contracts, uncovering new vulnerabilities and attack types using a severity score.  \nKEYWORDS  \nNatural language processing; Blockchain; Smart contracts; Smart contract security  \nSustainable Development Goals (SDG):  \nTABLE OF CONTENTS  \nStatement of Integrity ........................................................................................................ i  \nDedication ......................................................................................................................... ii  \nAcknowledgements .......................................................................................................... iii  \nAbstract ............................................................................................................................ iv  \nList of Figures................................................................................................................... vii  \nList of Tables................................................................................................................... viii  \nList of Abbreviations and Acronyms................................................................................. ix  \n1. Introduction.................................................................................................................. 1  \n2. Literature review ..............................................................","cbCailoK9lJbljnP","https://ap.wps.com/l/cbCailoK9lJbljnP","pdf",4199806,1,63,"English","en",105,"# Statement of Integrity\n# Dedication\n# Acknowledgements\n# Abstract\n# List of Figures\n# List of Tables\n# List of Abbreviations and Acronyms\n# Introduction\n# Literature review\n## Blockchain and smart contracts\n## Smart Contracts\n# Methodology\n## Data Collection","[{\"question\":\"What methods does the thesis use to study smart contract security?\",\"answer\":\"The thesis applies natural language processing together with unsupervised machine learning, specifically k-means and Latent Dirichlet Allocation, to analyze smart contract-related reports.\"},{\"question\":\"Which data sources are used for the analysis?\",\"answer\":\"The analysis uses reports from Code4Arena and incorporates real-world case studies and data from various blockchain platforms to inform the proposed framework.\"},{\"question\":\"What is the main output of the proposed security framework?\",\"answer\":\"The framework provides a pipeline that evaluates multiple smart contracts, uncovers vulnerabilities and attack types, and uses a severity score to support assessment.\"}]","Enhancing Smart Contract Security - A Machine Learning Framework Using Natural Language Processing and Unsupervised Techniques | PDF",1785734262,159,{"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},"enhancing-smart-contract-security-a-machine-learning-framework-using-natural-language-processing-and-unsupervised-techniques","",{"@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/enhancing-smart-contract-security-a-machine-learning-framework-using-natural-language-processing-and-unsupervised-techniques/121186/",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","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What methods does the thesis use to study smart contract security?","Question",{"text":75,"@type":76},"The thesis applies natural language processing together with unsupervised machine learning, specifically k-means and Latent Dirichlet Allocation, to analyze smart contract-related reports.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which data sources are used for the analysis?",{"text":80,"@type":76},"The analysis uses reports from Code4Arena and incorporates real-world case studies and data from various blockchain platforms to inform the proposed framework.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the main output of the proposed security framework?",{"text":84,"@type":76},"The framework provides a pipeline that evaluates multiple smart contracts, uncovers vulnerabilities and attack types, and uses a severity score to support assessment.","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"]