[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121198-en":3,"doc-seo-121198-105":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},121198,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","A Hybrid Framework To Secure IOT Sensor Networks Based On Blockchain And Machine Learning","Advances in sensor network technologies are expanding cyber-physical systems and Internet of Things smart objects, which also increases exposure to internal and external cyber-attacks. Conventional security approaches such as spread spectrum, cryptography, and key management may fail to detect attacks efficiently and can require complex software and hardware changes, limiting their effectiveness for IoT sensor network security. The dissertation proposes a hybrid security framework that uses blockchain to prevent attacks and machine learning to detect, verify, and examine incoming traffic for signs of malicious vulnerability.","University of North Dakota  \nUND Scholarly Commons  \n\n| Theses and Dissertations | Theses, Dissertations, and Senior Projects |\n| --- | --- |\n| May 2024\u003Cbr>A Hybrid Framework To Secure IOT Sensor Networks Based On Blockchain Andmachine Learning\u003Cbr>Shereen Ismail\u003Cbr>How does access to this work benefit you? Let us know!\u003Cbr>Follow this and additional works at: [https://commons.und.edu/theses](https://commons.und.edu/theses) |  |\n\nRecommended Citation  \nIsmail, Shereen, \"A Hybrid Framework To Secure IOT Sensor Networks Based On Blockchain Andmachine Learning\" (2024) . Theses and Dissertations. 6366.  \n[https://commons.und.edu/theses/6366](https://commons.und.edu/theses/6366)  \nThis Dissertation is brought to you for free and open access by the Theses, Dissertations, and Senior Projects at UND Scholarly Commons. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of UND Scholarly Commons. For more information, please contact [und.commons@library.und.edu](und.commons@library.und.edu).  \nA HYBRID FRAMEWORK TO SECURE IOT SENSOR NETWORKS BASED ON BLOCKCHAIN AND MACHINE LEARNING  \nShereen Ismail  \nDissertation submitted to the Faculty of the University of North Dakota  \nin partial fulfillment of the requirements for the degree of  \nDoctor of Philosophy  \nin  \nComputer Science  \nMay, 2024  \nGrand Forks, North Dakota  \nCopyright 2024 Shereen Ismail  \nDocuSign Envelope ID: 3C3D8B37-C1E2-4210-87A8-77279193DAFB  \nName: Shereen Ismail   \nDegree:  Doctor of Philosophy   \nThis document, submitted in partial fulfillment of the requirements for the degree from the University of North Dakota, has been read by the Faculty Advisory Committee under whom the work has been done and is hereby approved.  \n| Hassan Reza\u003Cbr> |\n| --- |\n| Hossein Salehfar\u003Cbr> |\n| Kouhyar Tavakolian\u003Cbr> |\n| Diana Dawoud |\n\n____________________________________  \nThis document is being submitted by the appointed advisory committee as having met all the requirements of the School of Graduate Studies at the University of North Dakota and is hereby approved.  \nChris Nelson  \nDean of the School of Graduate Studies 4/29/2024  \nDate  \niii  \nPermission  \nTitle: A HYBRID FRAMEWORK TO SECURE IOT SENSOR NETWORKS BASED ON BLOCKCHAIN AND MACHINE LEARNING  \nDepartment: Computer Science  \nDegree: Doctor of Philosophy  \nIn presenting this dissertation in partial fulfillment of the requirements for a graduate degree from the University of North Dakota, I agree that the library of this University shall make it freely available for inspection. I further agree that permission for extensive copying for scholarly purposes may be granted by the professor who supervised my dissertation work or, in his absence, by the chairperson of the department or the dean of the Graduate School. It is understood that any copying or publication or other use of this thesis or part thereof for financial gain shall not be allowed without my written permission. It is also understood that due recognition shall be given to me and to the University of North Dakota in any scholarly use which maybe made of any material in my dissertation.  \nShereen Ismail  \nDedication  \nTo the memory of my father  \nAbstract  \nWith the advances in sensor network technologies, more and more networked things, or smart objects, are being evolved in cyber-physical-based systems including Internet of Things. In recent years, Internet of Things Sensor Networks is a significant subject to a variety of internal and external cyber-attacks, necessitating the development of robust countermeasures tailored to their unique characteristics and limitations. Various prevention and detection techniques have been proposed to mitigate these attacks. Classical security techniques, such as spread spectrum, cryptography, and key management, may not efficiently detect attacks, and can demand sophisticated software and hardware changes, rendering these solutions insufficient to address Internet of Things Sensor Networks se","cbCaieKV6UETFwa0","https://ap.wps.com/l/cbCaieKV6UETFwa0","pdf",7223787,1,180,"English","en",105,"# 1 Introduction\n## 1.1 Motivation and Research Questions\n## 1.2 Objectives and Contributions\n## 1.3 Dissertation Organization\n## 1.4 Publications\n# 2 Literature Review\n## 2.1 Existing surveys on machine learning (ML) and blockchain (BC) in Wireless Sensor Network (WSN)\n## 2.2 WSN Security Requirements\n## 2.3 WSN Design Challenges and Unique Characteristics\n## 2.4 Cyber-attacks in WSNs\n## 2.5 Architecture of WSN vs. architecture of Intrusion Detection System (IDS)","[{\"question\":\"Why are classical security techniques insufficient for IoT sensor networks?\",\"answer\":\"Classical approaches like spread spectrum, cryptography, and key management may not efficiently detect attacks and can require sophisticated software and hardware changes.\"},{\"question\":\"What is the hybrid framework’s two-line defense mechanism?\",\"answer\":\"Blockchain is used for attack prevention, while machine learning is used for attack detection to verify incoming traffic and identify malicious behavior.\"},{\"question\":\"What happens if blockchain fails to prevent an attack?\",\"answer\":\"Machine learning verifies and examines the incoming traffic for signs of vulnerability, alerts the network to malicious attacks, and supports resilience against cyber-attacks.\"}]","A Hybrid Framework To Secure IOT Sensor Networks Based On Blockchain And Machine Learning | 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