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Intelligent Approach to Cyber Security provides details on the
important cyber security threats and its mitigation and the
influence of Machine Learning, Deep Learning and Blockchain
technologies in the realm of cyber security. Features: Role of Deep
Learning and Machine Learning in the Field of Cyber Security Using
ML to defend against cyber-attacks Using DL to defend against
cyber-attacks Using blockchain to defend against cyber-attacks This
reference text will be useful for students and researchers
interested and working in future cyber security issues in the light
of emerging technology in the cyber world.
Cyber Security Threats and Challenges Facing Human Life provides a
comprehensive view of the issues, threats, and challenges that are
faced in the cyber security domain. This book offers detailed
analysis of effective countermeasures and mitigations. The
financial sector, healthcare, digital manufacturing, and social
media are some of the important areas in which cyber-attacks are
frequent and cause great harm. Hence, special emphasis is given to
the study and analysis of cyber security challenges and
countermeasures in those four important areas. KEY FEATURES *
Discusses the prominence of cyber security in human life *
Discusses the significance of cyber security in the post-COVID-19
world * Emphasizes the issues, challenges, and applications of
cyber security mitigation methods in business and different sectors
* Provides comphrension of the impact of cyber security threats and
challenges in digital manufacturing and the internet of things
environment * Offers understanding of the impact of big data
breaches and future trends in data security This book is primarily
aimed at undergraduate students, graduate students, researchers,
academicians, and professionals who are interested in exploring
their research and knowledge in cyber security domain.
1. This book will attempt to provide a wide range of research and
development work under the umbrella of Intelligent Computing. Aim
of this book is to motivate research and applications of advanced
Intelligent Computing. This book will try to gather original
contributions from prospective authors specially solicited on
topics covered under broad areas such as Linguistic Computing,
Statistical Computing, Data Computing and Ambient Applications.
Some of the topics will cover industrial issues/applications and
academic research into intelligent computing. 2. Deep Learning
architectures are being increasingly used in day to day
applications where traditional machine learning and deep learning
algorithms were used. Their improved accuracy, effectiveness in
handling large data as well as reduced redundancy have major impact
on growing application in the relevant field creating a demand for
such a book in the market 3. This is an edited book that covers a
very wide are of AI applications, so it will be difficult to
specify principle competitive books. This book could be unique in
terms of the subject are that the book trying to cover
This book features selected papers presented at the 2nd
International Conference on Advanced Computing Technologies and
Applications, held at SVKM's Dwarkadas J. Sanghvi College of
Engineering, Mumbai, India, from 28 to 29 February 2020. Covering
recent advances in next-generation computing, the book focuses on
recent developments in intelligent computing, such as linguistic
computing, statistical computing, data computing and ambient
applications.
This book features selected papers presented at the 2nd
International Conference on Advanced Computing Technologies and
Applications, held at SVKM's Dwarkadas J. Sanghvi College of
Engineering, Mumbai, India, from 28 to 29 February 2020. Covering
recent advances in next-generation computing, the book focuses on
recent developments in intelligent computing, such as linguistic
computing, statistical computing, data computing and ambient
applications.
This book constitutes the refereed proceedings of the 26th Nordic
Conference on Secure IT Systems, NordSec 2021, which was held
online during November 2021.The 11 full papers presented in this
volume were carefully reviewed and selected from 29 submissions.
They were organized in topical sections named: Applied
Cryptography, Security in Internet of Things, Machine Learning and
Security, Network Security, and Trust.
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