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.