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Computational Intelligence in Data Science - 4th IFIP TC 12 International Conference, ICCIDS 2021, Chennai, India, March 18-20,... Computational Intelligence in Data Science - 4th IFIP TC 12 International Conference, ICCIDS 2021, Chennai, India, March 18-20, 2021, Revised Selected Papers (Hardcover, 1st ed. 2021)
Vallidevi Krishnamurthy, Suresh Jaganathan, Kanchana Rajaram, Saraswathi Shunmuganathan
R2,438 Discovery Miles 24 380 Ships in 18 - 22 working days

This book constitutes the refereed post-conference proceedings of the Fourth IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2021, held in Chennai, India, in March 2021. The 20 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers cover topics such as computational intelligence for text analysis; computational intelligence for image and video analysis; blockchain and data science.

Confluence of AI, Machine, and Deep Learning in Cyber Forensics (Hardcover): Sanjay Misra, Chamundeswari Arumugam, Suresh... Confluence of AI, Machine, and Deep Learning in Cyber Forensics (Hardcover)
Sanjay Misra, Chamundeswari Arumugam, Suresh Jaganathan, Saraswathi S
R6,205 Discovery Miles 62 050 Ships in 18 - 22 working days

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.

Computational Intelligence in Data Science - 4th IFIP TC 12 International Conference, ICCIDS 2021, Chennai, India, March 18-20,... Computational Intelligence in Data Science - 4th IFIP TC 12 International Conference, ICCIDS 2021, Chennai, India, March 18-20, 2021, Revised Selected Papers (Paperback, 1st ed. 2021)
Vallidevi Krishnamurthy, Suresh Jaganathan, Kanchana Rajaram, Saraswathi Shunmuganathan
R2,410 Discovery Miles 24 100 Ships in 18 - 22 working days

This book constitutes the refereed post-conference proceedings of the Fourth IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2021, held in Chennai, India, in March 2021. The 20 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers cover topics such as computational intelligence for text analysis; computational intelligence for image and video analysis; blockchain and data science.

Confluence of AI, Machine, and Deep Learning in Cyber Forensics (Paperback): Sanjay Misra, Chamundeswari Arumugam, Suresh... Confluence of AI, Machine, and Deep Learning in Cyber Forensics (Paperback)
Sanjay Misra, Chamundeswari Arumugam, Suresh Jaganathan, Saraswathi S
R4,771 Discovery Miles 47 710 Ships in 18 - 22 working days

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.

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