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Integrating artificial intelligence in cybersecurity and forensic practices
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Integrating artificial intelligence in cybersecurity and forensic practices/ Marwan Omar, Hewa Majeed Zangana, Derek Mohammed, editors.
其他作者:
Mohammed, Derek.
出版者:
Hershey, Pennsylvania :IGI Global, : 2025.,
面頁冊數:
1 online resource (xviii, 484 p.) :ill. :
標題:
Computer security. -
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3373-0588-2
ISBN:
9798337305905
Integrating artificial intelligence in cybersecurity and forensic practices
Integrating artificial intelligence in cybersecurity and forensic practices
[electronic resource] /Marwan Omar, Hewa Majeed Zangana, Derek Mohammed, editors. - Hershey, Pennsylvania :IGI Global,2025. - 1 online resource (xviii, 484 p.) :ill. - Advances in information security, privacy, and ethics (AISPE) book series. - Advances in information security, privacy, and ethics (AISPE) book series..
Includes bibliographical references and index.
Preface -- Chapter 1. Introduction to Artificial Intelligence in Cybersecurity and Forensic Science -- Chapter 2. The Role of Machine Learning and Deep Learning in Threat Detection -- Chapter 3. Using Natural Language Processing (NLP) for Phishing and Spam Detection -- Chapter 4. Network Forensics and Traffic Analysis With Machine Learning -- Chapter 5. Image Denoising Techniques for Cybersecurity and Forensic Applications: AI-Driven Approaches -- Chapter 6. AutomatedEvidence Collection and Analysis Using AI -- Chapter 7. How Human-Centered Cybersecurity (HCC) Training Fosters Organizational Cybersecurity Cultures (CSC) -- Chapter 8. The Role of Cybersecurity Legislation in Promoting Data Privacy -- Chapter 9. Digital Forensic Data Mining and Pattern Recognition -- Chapter 10. Improving AppSec Resiliency, Monitoring, Risk Assessment, and Compliance by Bridging DevSecOps With SOCs -- Chapter 11. An In-Depth Investigation on Hardware Trojans Testing Into Cyber Security Concerns Using Machine Learning Models -- Chapter 12. Source Code Analysis With Deep Neural Networks -- Chapter 13. An In-Depth Analysis of a Cyber Attack: Case Study and Security Insights -- Chapter 14. UsingMachine Learning to Identify High-Risk Employee Activity in Proactive Insider Threat Detection -- Compilation of References -- About the Contributors -- Index.
Integrating Artificial Intelligence in Cybersecurity and Forensic Practices explores the evolving role of AI in cybersecurity and forensic science. It delves into key AI techniques, discussing their applications, benefits, and challenges in tackling modern cyber threats and forensic investigations. Covering topics such as automation, deep neural networks, and traffic analysis, this book is an excellent resource for professionals, researchers, students, IT security managers, threat analysts, digital forensic investigators, and more.
Mode of access: World Wide Web.
ISBN: 9798337305905Subjects--Topical Terms:
557122
Computer security.
Subjects--Index Terms:
Artificial Intelligence (AI)Index Terms--Genre/Form:
554714
Electronic books.
LC Class. No.: QA76.9.A25 / I58 2025eb
Dewey Class. No.: 005.8
Integrating artificial intelligence in cybersecurity and forensic practices
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Preface -- Chapter 1. Introduction to Artificial Intelligence in Cybersecurity and Forensic Science -- Chapter 2. The Role of Machine Learning and Deep Learning in Threat Detection -- Chapter 3. Using Natural Language Processing (NLP) for Phishing and Spam Detection -- Chapter 4. Network Forensics and Traffic Analysis With Machine Learning -- Chapter 5. Image Denoising Techniques for Cybersecurity and Forensic Applications: AI-Driven Approaches -- Chapter 6. AutomatedEvidence Collection and Analysis Using AI -- Chapter 7. How Human-Centered Cybersecurity (HCC) Training Fosters Organizational Cybersecurity Cultures (CSC) -- Chapter 8. The Role of Cybersecurity Legislation in Promoting Data Privacy -- Chapter 9. Digital Forensic Data Mining and Pattern Recognition -- Chapter 10. Improving AppSec Resiliency, Monitoring, Risk Assessment, and Compliance by Bridging DevSecOps With SOCs -- Chapter 11. An In-Depth Investigation on Hardware Trojans Testing Into Cyber Security Concerns Using Machine Learning Models -- Chapter 12. Source Code Analysis With Deep Neural Networks -- Chapter 13. An In-Depth Analysis of a Cyber Attack: Case Study and Security Insights -- Chapter 14. UsingMachine Learning to Identify High-Risk Employee Activity in Proactive Insider Threat Detection -- Compilation of References -- About the Contributors -- Index.
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Integrating Artificial Intelligence in Cybersecurity and Forensic Practices explores the evolving role of AI in cybersecurity and forensic science. It delves into key AI techniques, discussing their applications, benefits, and challenges in tackling modern cyber threats and forensic investigations. Covering topics such as automation, deep neural networks, and traffic analysis, this book is an excellent resource for professionals, researchers, students, IT security managers, threat analysts, digital forensic investigators, and more.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3373-0588-2
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