Aims and Scope:

Wireless Sensor Networks (WSNs) comprise of numerous resource constrained nodes having capability of sensing, collecting and disseminating data in various applications. Sensor nodes in WSNs are resource constrained and often deployed in hostile environment making it susceptible to wide range of attacks. Recent advancements in WSNs, distributed intelligence for smart objects, enhanced communication protocols and several other communication solutions and technologies together enabled the birth of Internet of Things (IoT). IoT is a global ecosystem of communication technologies aimed at connecting any type of object, in any place, at any time to internet and also to each other. IoT realizes a vision in which billions of interconnected devices are deployed at all places ranging from within our bodies to very remote areas. This heterogeneity in the deployment nature of these devices raises several challenges especially in the field of security and privacy. Rapidly growing IoT will soon permeate to each and every aspect of our lives and therefore addressing IoT security threats is of utmost importance. IoT systems must be capable of protecting user privacy and addressing attacks such as denial of service attacks, eavesdropping, spoofing attack, jamming attack and many others. Traditional security approaches against the most prominent attacks are insufficient. Therefore, enabling the IoT devices to learn and adapt to various threats dynamically and addressing them proactively need immediate attention. In this regard, machine learning (ML) techniques are employed to address both intelligence and reconfigurability to various IoT devices. This book investigates the attack model for various IoT systems and explore various ML based IoT security solutions. Attacks in WSNs, IoT fundamentals, Security issues in IoT, Lightweight security protocols for IoT and sensor networks, ML techniques to foster communication security and privacy preserving using ML techniques are the major focus of this book. The book also discusses the challenges that needs to be addressed in order to implement these ML-based security techniques in practical IoT systems and WSNs.

Table of Contents:

This book follows a two-fold approach to discuss these aspects of security and privacy related to WSNs and IoT. On one hand, it presents the conceptual and core technical aspects that provide an insight of latest research trends and relevant theoretical framework in the field of sensor networks and IoT security. On the other hand, the book explains the machine learning based solutions for data security enhancement as a whole.

The approach used and the contributions made in this book are new and unique, and presents latest advances in the fields of WSNs and IoT. The content of this book, unlike currently available sources in the field, will significantly benefit a larger audience including young scholars, scientists, and researchers in both academia and industries as well as experts and specialists in the fields of WSNs and IoT.:

1) WSNs Fundamentals:Physical Sensors: Temperature, Mechanical, Magnetic, and Other, Sensor Networks; Wired and Wireless Sensor Systems: Signals, Transceivers, and Interfaces; Routing Techniques; Ad Hoc Networks; Sensor Network: Architecture and Protocol Design;MAC, Routing, and Transport Protocols in Sensor Networks.

2) Security and privacy in sensor networks: Security Threats; Biometric Systems; Healthcare Applications; Cryptography; Infrastructure Reliability; Authentication, Defence and Security; Wireless Surveillance; Visual Sensor Networks; Fault Tolerance and Diagnosis; Vulnerability and Privacy.

3) Security Issues and Defense Mechanisms in WSNs: Attacks and vulnerabilities in WSNs; Denial of service attack; Sybil attack; Jamming attack; Blackhole attack; Wormhole attack; Grey hole attack; Eavesdropping attack; Selective Forwarding attack and Hello Flood attack.

4) Integration of IoT and sensor networks: Case studies in WSNs and IoT; Lightweight security protocols for the IoT and sensor networks; MAC layer issues in Sensor Networks and IoT; Machine Learning for intrusion and malware detection in WSNs and IoT devices.

5) Survivable Path Routing in WSN for IoT applications: Wireless Network Protocols; Routing Techniques; Connectivity and Communication Scheduling; Tasking and Control; Statistical and Adaptive Signal Processing; Information Retrieval and Data Mining.

6) IoT: Fundamentals and challenges:Foundation of IoT; Logical and Physical Design protocols of IoT; Sensor deployment & Node discovery; Wearable sensors; Wireless Body Area Network (WBAN); Data acquisition; Robustness and reliability challenges.

7) Security issues of IoT: Foundation of threats in IoT environment; Key vulnerabilities in IoT systems — A holistic view; Attacks in IoT (Physical/MAC/Network); Algorithms, Protocol & Design for IoT-based security; Security Testbed for Internet-of-Things Devices.

8) IoT privacy challenges and solutions: Security and identity management for IoT; Mobile security infrastructure for IoT devices; Trust models in IoT; Applications and Limitations of IoT.

9) Case study on Future Generation IoT: Emerging wireless technologies for IoT-based Healthcare Systems; Software Defined Networking (SDN); Architectures and models for IoT-based Healthcare applications; Security, Privacy Issues and Challenges in IoT-based Healthcare Systems; Storage Issues and Challenges in IoT-based Healthcare Systems; Emerging e-Health IoT Applications; Integration of E-health and Internet of Things; Industry standards for IoT-security.

10) Privacy-preserving with ML: Machine Learning for intrusion and malware detection; Machine Learning in WSNs: Algorithms, Strategies, and Applications; Privacy-preserving with machine learning; Machine Learning approaches for improving IoT security; Threats and vulnerabilities identification through Machine Learning methods; Handling uncertainty in IoT design: Machine learning approach.

11) ML based IoT security schemes: ML techniques to foster communication security; Enhancing security through authentication using ML; Authentication and authorization processes with ML; Handling uncertainty in IoT design: Machine learning approach; ML based trust computational model for IoT services; ML based framework for mobile IoT security.

Publication Schedule:

The tentative schedule of the book publication is as follows:

Deadline for chapter proposal submission: August 20, 2019

Author notification for chapter proposal: August 30, 2019

Deadline for full chapter submission: September 30, 2020

Author notification: December 25, 2019

Camera-ready submission: January 31, 2020

Submission Procedure:

Authors are invited to submit original, high quality, unpublished results of Security and privacy issues in IoT devices and sensor networks: Machine learning to the rescue.

Submitted manuscripts should conform to the author’s guidelines of the Elsevier's chapter format of the Advances in ubiquitous sensing applications for healthcare Series, Elsevier series homepage (Link) Submitted chapters should be prepared using Latex or Microsoft Word, and according to the Elsevier's chapter templates that can be downloaded from the aforementioned website.

Prospective authors need to electronically submit their contributions using EasyChair submission system (EasyChair Submission).

Submitted manuscripts will be refereed by at least two independent and expert reviewers for quality, correctness, originality, and relevance. The accepted contributions will be published as a volume in the prestigious "Advances in ubiquitous sensing applications for healthcare Series, by Elsevier. More information about the "Advances in ubiquitous sensing applications for healthcare” series and the author instructions can be found in the Link.

Book Editors:

• Prof. (Dr.) Sudhir Kumar Sharma

Institute of Information Technology and Management,

D-29, Institutional Area, Janakpuri, New Delhi, India

Email: sharmasudhir08@gmail.com

• Bharat Bhushan, Ph.Dc,

Dept. of CSE, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India,

Email: bharat_bhushan1989@yahoo.com

• Prof. (Dr.) Narayan C. Debnath, Ph.D., D.Sc.,

School of Computing and Information Technology, Eastern International University, Vietnam, Email: NdebnathC@gmail.com