[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123801-en":3,"doc-seo-123801-105":31,"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":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},123801,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Assessing Blockchain’s Potential to Ensure Data Integrity and Security for AI and Machine Learning Applications","The increasing use of data-centric approaches in machine learning and artificial intelligence has intensified concerns about security, integrity, and data trustworthiness. Blockchain is presented as a practical countermeasure by leveraging its decentralized distributed ledger model and cryptographic mechanisms to support confidentiality and immutability. The study analyzes how blockchain can prevent unauthorized data manipulation during the ML training phase by forming valid data blocks, transmitting them via smart contracts, and using Proof of Work consensus with SHA256 signatures. Ethereum stores signatures while cloud infrastructure holds original datasets, enabling verification for stronger data quality and more reliable model outcomes.","Kennesaw State University  \nDigitalCommons@Kennesaw State University  \n\n| Master of Science in Information Technology Theses | Department of Information Technology |\n| --- | --- |\n| Fall 12-1-2023\u003Cbr>Assessing Blockchain’s Potential to Ensure Data Integrity and Security for AI and Machine Learning Applications\u003Cbr>Aiasha Siddika\u003Cbr>Kennesaw State University\u003Cbr>Follow this and additional works at: [https://digitalcommons.kennesaw.edu/msit_etd](https://digitalcommons.kennesaw.edu/msit_etd)\u003Cbr> Part of the Computer and Systems Architecture Commons |  |\n\nRecommended Citation  \nSiddika, Aiasha, \"Assessing Blockchain’s Potential to Ensure Data Integrity and Security for AI and Machine Learning Applications\" (2023) . Master of Science in Information Technology Theses. 16.  \n[https://digitalcommons.kennesaw.edu/msit_etd/16](https://digitalcommons.kennesaw.edu/msit_etd/16)  \nThis Thesis is brought to you for free and open access by the Department of Information Technology at DigitalCommons@Kennesaw State University. It has been accepted for inclusion in Master of Science in Information Technology Theses by an authorized administrator of DigitalCommons@Kennesaw State University. For more information, please [contact digitalcommons@kennesaw.edu](contact digitalcommons@kennesaw.edu).  \nAssessing Blockchain’s Potential to Ensure Data Integrity and Security for  \nAI and Machine Learning Applications  \nA Thesis Presented to  \nThe Faculty of Information Technology Department  \nby  \nAiasha Siddika  \nCommittee Members  \nDr. Liang Zhao (Chair)  \nDr. Seyedamin Pouriyeh (Committee Member) Dr. Xinyue Zhang (Committee Member)  \nIn Partial Fulfillment of Requirements for the Degree  \nMaster of Science in Information Technology  \nKennesaw State University Kennesaw, Georgia  \nDecember 2023  \nAcknowledgments  \nI would like to take this opportunity to express my sincere gratitude to everyone who has helped me along the way with my thesis. Throughout my academic journey, I have found inspiration, strength, and enlightenment in Allah’s unfailing direction. With his blessings, my path has been lighted, enabling me to successfully complete this task.  \nI would like to express my gratitude to Dr. Liang Zhao, my thesis adviser, for his steadfast support, priceless advice, and endless patience. His knowledge and guidance have greatly influenced the direction of my study.  \nI owe my family a huge debt of gratitude for their unwavering encouragement, support, and faith in my potential. Their steadfast belief in me has served as a continual source of inspiration. In addition, I would like to thank my friends and colleagues for being a source of support and inspiration throughout my academic journey. The concepts put forward in this thesis have been greatly influenced by their conversations, advice, and support.  \nFurthermore, I would like to thank all of the study participants and contributors whose assistance and wisdom have been crucial in obtaining the data and information required for this project.  \nFinally, I want to express my gratitude to everyone who has helped along the way, whether directly or indirectly. Your encouragement, support, and contributions have been crucial to this thesis’s successful completion.  \nAbstract  \nThe increasing use of data-centric approaches in the fields of Machine Learning and Artificial Intelligence (ML/AI) has raised substantial issues over the security, integrity, and trustworthiness of data. In response to this challenge, Blockchain technology offered a promising and practical solution, as its inherent characteristics as a decentralized distributed ledger, coupled with cryptographic processes, offer an unprecedented level of data confidentiality and immutability. This study examines the mutually beneficial connection between Blockchain technology and ML/AI, using Blockchain’s inherent capacity to protect against unauthorized alterations of data during the training phase of ML models. The method involves building valid block","cbCaic9lrgHDYYnJ","https://ap.wps.com/l/cbCaic9lrgHDYYnJ","pdf",3311376,2,1,41,"English","en",105,"# Introduction\n## Motivation and Challenges\n## Research Aim\n# Literature Review\n# Methodology and Framework\n# Framework Development\n# Recommendations and Future Prospects\n## Insights and Roadmap for the Future\n## Integration of Proof of Federated Learning (PoFL)\n## Collaborative Secure Computing Integration\n# Conclusion","[{\"question\":\"How does the thesis use blockchain to protect data during ML model training?\",\"answer\":\"It builds valid blocks from the training dataset and sends them to the mining process through smart contracts, preventing unauthorized changes during the training phase.\"},{\"question\":\"What role do smart contracts and Proof of Work (PoW) play in the proposed method?\",\"answer\":\"Smart contracts coordinate the transmission of data blocks to the mining process, while Proof of Work is used as the consensus mechanism for the blockchain process.\"},{\"question\":\"How are SHA256 and the Ethereum blockchain used in the data verification process?\",\"answer\":\"SHA256 generates cryptographic signatures for each data block, and a public Ethereum blockchain stores these signatures so the training-phase data can be verified.\"}]","Assessing Blockchain’s Potential to Ensure Data Integrity and Security for AI and Machine Learning Applications | 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