Book Image

Practical Industrial Internet of Things Security

By : Sravani Bhattacharjee
Book Image

Practical Industrial Internet of Things Security

By: Sravani Bhattacharjee

Overview of this book

Securing connected industries and autonomous systems is of primary concern to the Industrial Internet of Things (IIoT) community. Unlike cybersecurity, cyber-physical security directly ties to system reliability as well as human and environmental safety. This hands-on guide begins by establishing the foundational concepts of IIoT security with the help of real-world case studies, threat models, and reference architectures. You’ll work with practical tools to design risk-based security controls for industrial use cases and gain practical knowledge of multi-layered defense techniques, including identity and access management (IAM), endpoint security, and communication infrastructure. You’ll also understand how to secure IIoT lifecycle processes, standardization, and governance. In the concluding chapters, you’ll explore the design and implementation of resilient connected systems with emerging technologies such as blockchain, artificial intelligence, and machine learning. By the end of this book, you’ll be equipped with the all the knowledge required to design industry-standard IoT systems confidently.
Table of Contents (22 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Foreword
Contributors
Disclaimer
Preface
I
I
Index

Cognitive countermeasures – AI, machine learning, and deep learning


Cognitive computing is highly relevant and increasingly indispensable to industrial IoT use cases, where machines can make autonomous decisions based on IoT device data, and can also protect themselves against external threats and malicious attacks. This may not be merely sci-fi imagination, as it was a decade ago.

Computer visionaries such as Alan Turing were optimistic about artificial intelligence (AI) since the 1950s. However, the recent spike in interest and research on AI owe to faster, cheaper, and more powerful parallel processing using GPUs, coupled with a steady growth in data sciences. Pure AI—where machines and robots can operate and decide with full autonomy—is still a long way away. However, practical AI, where cognitive computing augments human expertise, is already a reality. Machine learning and its specialized branch, called deep learning, are currently the main drivers behind cognitive IoT and practical...