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Cybersecurity for industry 4.0 : analysis for design and manufacturing
Thames L., Schaefer D., Springer International Publishing, New York, NY, 2017. 265 pp. Type: Book (978-3-319506-59-3)
Date Reviewed: Jan 4 2018

Industry 4.0 is a term that describes what is often called the fourth industrial revolution. The first three were mechanization, mass production, and computers and automation. The fourth is the cyber-physical revolution, which integrates information technology (IT) with operational technology (OT). The opening chapter overviews the key benefits, technologies, and challenges of Industry 4.0 (also referred to as IIoT).

Industry 4.0 includes smart factories that are driven by intelligent cyber-physical systems (CPS) that enable such capabilities as self-monitoring, self-configuration, and self-healing.

Cloud-based design and manufacturing (CBDM) is an essential part of this process. CBDM contains all the key aspects of cloud computing, “including on-demand self-service, ubiquitous network access, rapid scalability, resource pooling, and virtualization,” according to the book. The software-defined cloud manufacturing (SDCM) architecture is part of this process.

However, all the advances of Industry 4.0 come with the price of increased cyber-security risks. For example, ubiquitous communication systems may now allow OT devices such as a PLC to be hacked as there is no longer an air gap, which isolated the device from an IT network. Each of the chapters in the book after the opening one address a specific issue regarding cyber-security risks.

Encryption for cloud-enabled collaborative product development is the subject of the second chapter. Collaborative product development via cloud requires that product information should be shared flexibly among collaborators. Maintaining the security of sensitive intellectual property information of computer-aided design (CAD) models is necessary for effective collaboration. The chapter describes an approach to flexibly encrypt CAD models in a collaborative product development environment.

The next chapter discusses a new approach to cyberphysical security and advanced digital manufacturing. In digital manufacturing, “both the central design computer and the remote manufacturing equipment” must be protected. The secure manufacturing information architecture described “relies on fine-grained, role-based controls,” which work well within and between organizations.

Smart manufacturing and smart factories via IIoT connect more and more devices via a network and lead to a huge increase in the volume of data from a large number of sources. In particular, supervisory control and data acquisition (SCADA) systems are vulnerable due to the increased number of entry points as well as weaknesses within the systems themselves. Examining security incidents via a forensic analysis is especially necessary for SCADA systems. This chapter discusses a SCADA system forensic analysis process within IIoT, including a forensic response model.

Healthcare-based sensors, such as on wearable medical devices, are collecting an enormous quantity of rich information that indicates our physical and mental health. This chapter proposes a secure IIoT architecture to manage that enormous quantity of data (called big data) for healthcare applications. That architecture uses a key management security mechanism to protect big data.

The following chapter offers “a conceptual model and operation mechanism of decentralized cyber-physical systems (CPS).” That includes a cloud-based smart manufacturing paradigm that uses “a cloud-based agent approach to create an intelligent collaborative environment for product creation.”

The succeeding chapter focuses on applying processing cyber security controls for direct digital manufacturing (DDM) systems. The authors believe that DDM systems are an on-demand technology that can bring significant “advances to supply chains, consumer goods, and economic growth.” However, this technology brings with it the creation of new cyber-attack vector scenarios that can have damaging effects, for example, to supply chains. This chapter deals with those issues.

An inference-based intrusion detection system for industrial control systems (ICS) security is discussed next. This is followed by a discussion of the practical security aspects of IoT. The book concludes with a description of how cyberattack detection and response can be incorporated into an SDCM architecture.

Collectively, the edited papers that comprise the book provide a useful examination of the issues of cybersecurity for Industry 4.0. Therefore, IT and OT readers who deal with these types of security issues should find the book useful.

Reviewer:  David G. Hill Review #: CR145752 (1803-0143)
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