An Interdisciplinary Approach to Modern Network Security

1. Auflage 2022
ISBN: 978-0-367-70608-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 216 Seiten, Format (B × H): 160 mm x 242 mm, Gewicht: 462 g

An Interdisciplinary Approach to Modern Network Security presents the latest methodologies and trends in detecting and preventing network threats. Investigating the potential of current and emerging security technologies, this publication is an all-inclusive reference source for academicians, researchers, students, professionals, practitioners, network analysts and technology specialists interested in the simulation and application of computer network protection. It presents theoretical frameworks and the latest research findings in network security technologies, while analyzing malicious threats which can compromise network integrity. It discusses the security and optimization of computer networks for use in a variety of disciplines and fields.

Touching on such matters as mobile and VPN security, IP spoofing and intrusion detection, this edited collection emboldens the efforts of researchers, academics and network administrators working in both the public and private sectors. This edited compilation includes chapters covering topics such as attacks and countermeasures, mobile wireless networking, intrusion detection systems, next-generation firewalls, web security and much more.

Information and communication systems are an essential component of our society, forcing us to become dependent on these infrastructures. At the same time, these systems are undergoing a convergence and interconnection process that has its benefits, but also raises specific threats to user interests. Citizens and organizations must feel safe when using cyberspace facilities in order to benefit from its advantages. This book is interdisciplinary in the sense that it covers a wide range of topics like network security threats, attacks, tools and procedures to mitigate the effects of malware and common network attacks, network security architecture and deep learning methods of intrusion detection.

Zielgruppe

Postgraduate and Professional

Autoren/Hrsg.

Sharma, Anand

Pramanik, Sabyasachi

Le, Dac-Nhuong

Bhatia, Surbhi

Fachgebiete

• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Datensicherheit, Datenschutz
• Mathematik | Informatik EDV | Informatik Digital Lifestyle Internet, E-Mail, Social Media
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerkprotokolle

Inhaltsverzeichnis

Chapter 1: Application of Artificial Intelligence in Cyber-security – A Detail Survey on Intrusion Detection System

Chapter 2: IoMT data Security Approach: Blockchain in Healthcare

Chapter 3: Machine Learning Approach for Network Intrusion Detection System

Chapter 4: Deep learning approach for network intrusion detection system

Chapter 5: Firewalls and Security

Chapter 6: Application of Machine Learning and Deep Learning in Cyber Security: An Innovative Approach

Chapter 7: A Modified Authentication Approach for Cloud computing in E-Healthcare System

Chapter 8: Advanced Security System in Video Surveillance for COVID-19

Chapter 9: Secure Sound and Data Communication via Li-Fi

Chapter 10: A Novel Secured Method for Rapid Data Accumulation in Energy Aware WSN

Über Autor(innen)

Editor #1 Dr. Sabyasachi Pramanik, Assistant Professor, Department of Computer Science & Engineering, Haldia Institute of Technology, India
Editor #2 Dr. Anand Sharma, Assistant Professor, Department of Computer Science and Engineering, Mody University, India
Editor #3 Dr. Surbhi Bhatia, Assistant Professor, Department of Information Systems, College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia.
Editor #4 Dr. Dac-Nhuong Le, Associate Professor in Computer Science, Deputy-Head of Faculty of Information Technology, Haiphong University, Vietnam