Book Image

Architecting the Industrial Internet

By : Robert Stackowiak, Shyam Varan Nath, Carla Romano
Book Image

Architecting the Industrial Internet

By: Robert Stackowiak, Shyam Varan Nath, Carla Romano

Overview of this book

The Industrial Internet or the IIoT has gained a lot of traction. Many leading companies are driving this revolution by connecting smart edge devices to cloud-based analysis platforms and solving their business challenges in new ways. To ensure a smooth integration of such machines and devices, sound architecture strategies based on accepted principles, best practices, and lessons learned must be applied. This book begins by providing a bird's eye view of what the IIoT is and how the industrial revolution has evolved into embracing this technology. It then describes architectural approaches for success, gathering business requirements, and mapping requirements into functional solutions. In a later chapter, many other potential use cases are introduced including those in manufacturing and specific examples in predictive maintenance, asset tracking and handling, and environmental impact and abatement. The book concludes by exploring evolving technologies that will impact IIoT architecture in the future and discusses possible societal implications of the Industrial Internet and perceptions regarding these projects. By the end of this book, you will be better equipped to embrace the benefits of the burgeoning IIoT.
Table of Contents (19 chapters)
Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Securing the backend


We will now turn our attention to strategies for securing the backend components. The following diagram indicates the components we will consider, as shown in the shaded area:

Figure 8.6: Backend Security

The streaming analytics engines provide a location to deploy applications, such as those that apply machine learning algorithms, on transient data. The security mechanisms for streaming analytics engines are less sophisticated today when compared to the data-management systems (such as the data lake, data warehouse, and data mart that are pictured). This is due, in part, to the limited requirements for administrative capabilities, but also due to streaming analytics engines being relatively new.

The primary means for assuring secure streaming analytics is through authentication using methods that can include using Kerberos, LDAP, or Active Directory. Authorization is generally tied to authorized logins for initiating applications. Once the credentials are verified and...