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Confluence of AI, machine, and deep ...

Misra, Sanjay.

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Confluence of AI, machine, and deep learning in cyber forensics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Confluence of AI, machine, and deep learning in cyber forensics/ Sanjay Misra, Chamundeswari Arumugam, Suresh Jaganathan, and Shunmuganathan Saraswathi.
其他題名:	Confluence of artificial intelligence, machine, and deep learning in cyber forensics
其他作者:	Misra, Sanjay.
出版者:	Hershey, Pennsylvania :IGI Global, : 2021.,
面頁冊數:	1 online resource (xix, 248 p.)
內容註:	Chapter 1. A comprehensive perspective on mobile forensics: process, tools, and future trends -- Chapter 2. Applications of machine learning in cyber forensics -- Chapter 3. Machine learning forensics: a new branch of digital forensics -- Chapter 4. Crucial role of data analytics in the prevention and detection of cyber security attacks -- Chapter 5. Deep learning approaches to overcome challenges in forensics -- Chapter 6. Deep learning-based malware detection and classification -- Chapter 7. Detecting fake news using deep learning and NLP -- Chapter 8. Impediments in mobile forensics -- Chapter 9. Use-case of blockchain in cybercrime and cyberattack -- Chapter 10. Motivational quotes-based intelligent insider threat prediction model -- Chapter 11. Challenges of developing AI applications in the evolving digital world and recommendations to mitigate such challenges: a conceptual view -- Chapter 12. Challenges in developing software in today's scenario: an analysis at developmental stage level.
標題:	Computer crimes - Investigation. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-4900-1
ISBN:	9781799849018 (ebk.)

Confluence of AI, machine, and deep learning in cyber forensics
Confluence of AI, machine, and deep learning in cyber forensics[electronic resource] /Confluence of artificial intelligence, machine, and deep learning in cyber forensics Sanjay Misra, Chamundeswari Arumugam, Suresh Jaganathan, and Shunmuganathan Saraswathi. - Hershey, Pennsylvania :IGI Global,2021. - 1 online resource (xix, 248 p.)

Includes bibliographical references and index.

Chapter 1. A comprehensive perspective on mobile forensics: process, tools, and future trends -- Chapter 2. Applications of machine learning in cyber forensics -- Chapter 3. Machine learning forensics: a new branch of digital forensics -- Chapter 4. Crucial role of data analytics in the prevention and detection of cyber security attacks -- Chapter 5. Deep learning approaches to overcome challenges in forensics -- Chapter 6. Deep learning-based malware detection and classification -- Chapter 7. Detecting fake news using deep learning and NLP -- Chapter 8. Impediments in mobile forensics -- Chapter 9. Use-case of blockchain in cybercrime and cyberattack -- Chapter 10. Motivational quotes-based intelligent insider threat prediction model -- Chapter 11. Challenges of developing AI applications in the evolving digital world and recommendations to mitigate such challenges: a conceptual view -- Chapter 12. Challenges in developing software in today's scenario: an analysis at developmental stage level.

"The book provides original research about cyber forensics and its relationship to Artificial Intelligence (AI) and presents the results of research and case studies that advance the practice and understanding of cyber forensics methods and techniques to support efficient and effective investigations. It covers a variety of topics, including forensic analysis, cloud forensics, forensics storage, mobile device forensics, forensic reporting, forensics tools, and more"--

ISBN: 9781799849018 (ebk.)Subjects--Topical Terms:

622656
Computer crimes
--Investigation.

LC Class. No.: HV8079.C65 / C66 2021

Dewey Class. No.: 363.250285/63

Confluence of AI, machine, and deep learning in cyber forensics
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246 3 $a Confluence of artificial intelligence, machine, and deep learning in cyber forensics
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300 $a 1 online resource (xix, 248 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. A comprehensive perspective on mobile forensics: process, tools, and future trends -- Chapter 2. Applications of machine learning in cyber forensics -- Chapter 3. Machine learning forensics: a new branch of digital forensics -- Chapter 4. Crucial role of data analytics in the prevention and detection of cyber security attacks -- Chapter 5. Deep learning approaches to overcome challenges in forensics -- Chapter 6. Deep learning-based malware detection and classification -- Chapter 7. Detecting fake news using deep learning and NLP -- Chapter 8. Impediments in mobile forensics -- Chapter 9. Use-case of blockchain in cybercrime and cyberattack -- Chapter 10. Motivational quotes-based intelligent insider threat prediction model -- Chapter 11. Challenges of developing AI applications in the evolving digital world and recommendations to mitigate such challenges: a conceptual view -- Chapter 12. Challenges in developing software in today's scenario: an analysis at developmental stage level.
520 3 $a "The book provides original research about cyber forensics and its relationship to Artificial Intelligence (AI) and presents the results of research and case studies that advance the practice and understanding of cyber forensics methods and techniques to support efficient and effective investigations. It covers a variety of topics, including forensic analysis, cloud forensics, forensics storage, mobile device forensics, forensic reporting, forensics tools, and more"-- $c Provided by publisher.
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