Confluence of AI, Machine, and Deep Learning in Cyber Forensics

ISBN 10: 1799849007 / ISBN 13: 9781799849001

Verlag: Information Science Reference, 2020

Beschreibung

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents cutting-edge research on the latest AI techniques being used to design and build solutions that address prevailing issues in cyber forensics and that will support effective investigations. The book explores the value of the deep learning algorithm .

Bestandsnummer des Verkäufers 448342590

Bibliografische Details

• Titel: Confluence of AI, Machine, and Deep Learning in Cyber Forensics
• Verlag: Information Science Reference
• Erscheinungsjahr: 2020
• Sprache: Englisch
• ISBN-10: 1799849007
• ISBN-13: 9781799849001
• Einband: Hardcover
• Zustand: New
• Verkäuferkataloge:
  • Importe

Über diesen Titel

Inhaltsangabe

Developing a knowledge model helps to formalize the difficult task of analyzing crime incidents in addition to preserving and presenting the digital evidence for legal processing. The use of data analytics techniques to collect evidence assists forensic investigators in following the standard set of forensic procedures, techniques, and methods used for evidence collection and extraction. Varieties of data sources and information can be uniquely identified, physically isolated from the crime scene, protected, stored, and transmitted for investigation using AI techniques. With such large volumes of forensic data being processed, different deep learning techniques may be employed. Confluence of AI, Machine, and Deep Learning in Cyber Forensics contains cutting-edge research on the latest AI techniques being used to design and build solutions that address prevailing issues in cyber forensics and that will support efficient and effective investigations. This book seeks to understand the value of the deep learning algorithm to handle evidence data as well as the usage of neural networks to analyze investigation data. Other themes that are explored include machine learning algorithms that allow machines to interact with the evidence, deep learning algorithms that can handle evidence acquisition and preservation, and techniques in both fields that allow for the analysis of huge amounts of data collected during a forensic investigation. This book is ideally intended for forensics experts, forensic investigators, cyber forensic practitioners, researchers, academicians, and students interested in cyber forensics, computer science and engineering, information technology, and electronics and communication.

Über die Autorinnen und Autoren

Dr. Sanjay Misra , a distinguished Senior Member of IEEE and ACM Distinguished Lecturer (21-24), currently serves as a Senior Scientist at the Institute for Energy Technology (IFE) in Halden, Norway. Previously, he held positions within the Computer Science and Communication department at Østfold University College, also in Halden. Dr. Misra holds a Ph.D. in Information and Knowledge Engineering (Software Engineering) from the University of Alcala, Spain, and an M.Tech. in Software Engineering from MLN National Institute of Technology, India. His expertise spans Applied Informatics, encompassing Software Engineering Applications, Cyber Security, Health Informatics, and Intelligent Systems utilizing AI and computational techniques. With an impressive publication record, including around 150 JCR/SCIE articles in prestigious journals such as Computers & Security and Engineering Applications of Artificial Intelligence, Dr. Misra consistently ranks among the top 2% of scientists globally, as recognized by Stanford University. He has received numerous awards for his outstanding contributions, including the 2014 IET Software Premium Award (UK). Dr. Misra serves as Editor-in-chief and editor of multiple international journals, including the International Journal of Human Capital & Information Technology Professionals(EIC, IF. 1.9), Nature: Scientific Report((Impact Factor: 4.996), Elsevier: Alex. Engineering((Impact Factor: 6.8, Q1)), General chairs of several IEEE and Springer conferences and has edited numerous special issues and authored over 100 books and conference proceedings. A sought-after speaker, he has delivered over 100 keynotes and invited talks at prestigious conferences and institutes across more than 60 countries.

Chamundeswari Arumugam is a Professor of Computer Science and Engineering department at Sri Sivasubramaniya Nadar College of Engineering, Chennai, India.

Suresh Jaganathan , Associate Professor in the Department of Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, has more than 22 years of teaching experience. He received his PhD in Computer Science from Jawaharlal Nehru Technological University, Hyderabad, M.E Software Engineering from Anna University and B.E Computer Science & Engineering, from Madurai Kamarajar University, Madurai. He has more than 30 publications in refereed International Journals and Conferences. Apart from this, to his credit, he has filed two patents and written a book on “Cloud Computing: A Practical Approach for Learning and Implementation”, published by Pearson Publications. He is an active reviewer in reputed journals (Elsevier - Journal of Networks and Computer Applications, Computer in Biology and Medicine). His areas of interest are Distributed Computing, Deep Learning, Data Analytics, Machine learning & Blockchain Technology.

Saraswathi S. , Associate Professor in the Department of Computer Science and Engineering has around 16 years of teaching experience. She received her Ph.D. from Anna University in 2015, Masters in Computer Science & Engineering (M.E.) from Manonmaniam Sundaranar University in 2005 and Bachelor in Computer Science & Engineering (B.E.) from National Engineering College, Manonmaniam Sundaranar University in 1999. She is a member of ACM and IEEE. She has two faculty internal funded projects funded by SSN trust. Her area of research includes Network Security, Cryptography, Cyber Forensic and IOT.