[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122332-en":3,"doc-seo-122332-105":30,"detail-sidebar-cat-0-en-105":92},{"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},122332,2336464648746,"Skyler","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Malware detection using machine learning - Master of Science thesis","This Master of Science thesis presents a study on malware detection using machine learning, framed through a structured research problem, aims, objectives, and research questions. The work reviews prior literature on malware detection models and methods, including symptoms, malware analysis techniques, behavior- and signature-based approaches, and key challenges. It outlines a methodology distinguishing antimalware versus antivirus, surveys anti-malware techniques and malware learning techniques, and describes algorithms and design considerations. The dataset chapter focuses on malware datasets and removing noisy features to support effective model training.","California State University, NORTHRIDGE  \nMalware detection using machine learning  \nA thesis submitted in partial fulfilment of the requirements For the degree of Master of Science, In Computer Science  \nBy  \nNaveen Donepudi  \nDecember 2022  \nThe thesis of Naveen Donepudi is approved  \n X   \nDr. Robert McIlhenny  \n X   \nDate  \nX  \nDr. Jeff Wiegley  \nX  \nDr. Wonjun Lee , Chair  \nX  \nDate  \nX  \nDate  \nCalifornia State University Northridge  \nAcknowledgement  \nI would like to thank to my lovely parents and my hard-working mentors who supported me alot to perform and complete my thesis with perfection. Moreover, I also pay special thanks to the committee chair persons that include a penal of doctors and professors of California State University Northridge’s College of Engineering and computer science. I was able to complete my thesis only due to my hard work and diligent support and services from my teachers. The all supported me a lot and give me confidence to meet my goals over the course and also complete my thesis at high. Overall, my parents, and teachers had played a crucial role for completing my work on time and with comprehensive information.  \nAlthough my mentors and friends were extremely loyal towards my goal. Therefore, they have make sure that all points in the thesis are completed by me without any difficulty. These members deserve my high success rank. It is only due to their sincere efforts and struggle so thanks to them a lot from my side.  \nIn the end, I would like to thanks to my parents, who were extremely sincere and loyal with meat every stage of my career. My parents were always there to support me in difficulty times. I was able to complete my thesis due to their efforts too. My parents are my real support my pillars.  \nTable of Contents  \nSignature Page ……………………………………………………………………………………….... ii  \nAcknowledgement ................................................................................................................... iii  \nList of figures ...........................................................................................................................vii  \nAbstract .................................................................................................................................. viii  \nChapter 1 Introduction ............................................................................................................... 1  \n1.1. Introduction ................................................................................................................. 1  \n1.2. Problem statement .......................................................................................................2  \n1.3. Aims and objectives ....................................................................................................3  \n1.4. Background .................................................................................................................4  \n1.5. Research questions ......................................................................................................4  \n1.6. Research Framework...................................................................................................4  \n1.7. Research Significance ................................................................................................. 5  \n1.8. Summary ..................................................................................................................... 5  \nChapter 2: Review of literature ..................................................................................................6  \n2.1. Introduction ..................................................................................................................... 6  \n2.2. Background study ...........................................................................................................6  \n2.3. Proposed models and methods........................................................................................7  \n2.","cbCailfAWRxdVGVD","https://ap.wps.com/l/cbCailfAWRxdVGVD","pdf",711116,1,54,"English","en",105,"# Chapter 1 Introduction\n## 1.1 Introduction\n## 1.2 Problem statement\n## 1.3 Aims and objectives\n## 1.4 Background\n## 1.5 Research questions\n## 1.6 Research Framework\n## 1.7 Research Significance\n## 1.8 Summary\n# Chapter 2 Review of literature\n## 2.1 Introduction\n## 2.2 Background study\n## 2.3 Proposed models and methods\n# Chapter 3 Methodology\n## 3.1 Introduction\n## 3.2 Overview of the methodology\n## 3.3 Difference between antimalware and antivirus\n## 3.4 Anti-Malware Technique\n## 3.5 Antimalware service executable (AMSE)\n## 3.6 Traditional Anti-malware Techniques\n## 3.7 Malware Learning Techniques\n## 3.8 Algorithms\n## 3.9 Why machine learning\n## 3.10 Analysis and design\n# Chapter 4 Dataset\n## 4.1 Malware Datasets\n## 4.2 Eliminating Noisy Features","[{\"question\":\"What problem does the thesis address in malware detection?\",\"answer\":\"The thesis defines a problem statement for malware detection and frames it with aims, objectives, background, and research questions to guide the study.\"},{\"question\":\"How does the methodology distinguish between antimalware and antivirus?\",\"answer\":\"The methodology section includes an explicit comparison between antimalware and antivirus, followed by coverage of anti-malware techniques and related executable concepts.\"},{\"question\":\"What does the dataset chapter focus on?\",\"answer\":\"The dataset chapter discusses malware datasets and techniques for eliminating noisy features to improve the quality of inputs used for learning and analysis.\"}]","Malware detection using machine learning - 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