Dr. Ranjit Panigrahi received his Master of Technology in Computer Sciences & Engineering at Sikkim Manipal Institute of Technology, Sikkim and PhD degree in Computer Applications from Sikkim Manipal University. At present, he is deputed as Assistant Professor - Selection Grade in Department of Computer Applications in Sikkim Manipal Institute of Technology, Sikkim, India. His area of research includes machine learning, biomedical engineering. He is also a certified Microsoft Technology Specialist. At Sikkim Manipal Institute of technology his roles and responsibilities include -
This book calls chapters based on recent state-of-the art edge artificial intelligence approaches used for enhanced cyber defense mechanisms to handle big data. Chapters should provide a glimpse of computational intelligence techniques and automated reasoning models capable of fast training and timely data processing of cybersecurity big data. Apart from edge artificial intelligence techniques, this book also calls chapters related to reviews of recent cyber threats and attacks and their countermeasures. Chapters solicited for this book are -
Chapter 1. A Brief introduction to cyber threats and related countermeasures
This chapter will be dealt with a brief introduction of Cyber Defense Systems that has been outlined highlighting the modern threats and attacks in various network environments such as host-based network-based, smart grid. An emphasis will be given to categorize and presents a detailed taxonomy of cyber threats according to the source of origination and location. A brief introduction of the latest available defense mechanisms is also discussed in this chapter. As an introductory chapter, these topics enlighten the readers with a brief idea of current threats found in the cyber arena.
Chapter 2. Edge Artificial Intelligence - An Overview
This chapter will be a brief introduction to Edge Artificial Intelligence. The chapter aims to deliver advantages of EdgeAI; viz., real-time operations, reduced power consumption, decreased data communication cost, and increased privacy. It is also intended to deliver the role of EdgeAI to handle cybercrimes and related threats. The role of EdgeAI will also be analyzed looking forward, how effectively it allows the network topology to be fault-tolerant even in the influence of attacks.
Chapter 3. Reviews of EdgeAI based Cyber Defense Mechanisms
This chapter will provide a brief survey of state-of-art EdgeAI based Cyber Defense Mechanisms (CDMs). Various CDMs are explored based on detection type and approaches. Emphasis will be given to those methods that integrate signature based CDMs in the process of detection. Moreover, many modern embedded EdgeAI based methods will be explored that acts as the front line of defense in the network environment. Further, a detailed taxonomy of CDMs datasets that are huge and contains recent attack trends will be explored elaborating the target environment.
Chapter 4 to Chapter 15. Contributory Chapters from prospective authors
All 11 chapters will be dealt with specific challenging areas pertaining to cyber defense through Edge AI. We are inviting chapters from you in the following 11 areas, including but not limited to
Important Dates
Chapters Submission: August 30, 2021 (On or before)
Review Notification: September 30, 2021 (On or before)
Camera Ready Submission: October 30, 2021 (On or before)
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