This post was written by Peter Fuhr, PhD, Marissa Morales-Rodriguez, PhD, Sterling Rooke, PhD, and Penny Chen, PhD.

Industrial instrumentation and sensors are purpose-built for applications. Rugged and proven for field applications in harsh environments, such as on an oil platform or in a copper mine 5,000-feet below ground, these instruments require reliability and performance. Before the turn of the millennium, industrial technology-and information technology (IT) in particular-drove these systems, and they often exceeded the abilities of consumer products. However, as we stand today, commercial Internet of Things (IoT) technology has advanced rapidly, with industrial control systems lagging in intelligence and features.

Experienced owner-operators of industrial facilities recognize the buzz surrounding the Industrial Internet of Things (IIoT), but often shun the notion of consumer-grade devices being installed and integrated into an operational control system. At an ISA Process Control and Safety (PCS) conference, ISA's Communication Division convened a panel to focus on IIoT.

Experienced industrial and control engineers on the panel expressed concerns and reservations with IIoT. Whereas some acknowledged an interest in the topic, others did not recognize it as an inevitable part of the industrial controls landscape. Granted, IIoT is still mostly a vision in the instrumentation and automation landscape; however, its place on stage is coming into view. During the opening session, then ISA President Jim Keaveney rhetorically asked the audience if IoT had peaked and also wondered if "cyber" would be the next area for innovation. This blog explores the nexus of "domestic" IoT and how product evolution will drive its development toward that of IIoT.

U.S. government to promote IIoT evolution?

At a National Telecommunications and Information Administration (part of the U.S. Department of Commerce) IoT workshop, discussions included how IoT and IIoT were set to converge around common threads. An important area of convergence will occur around onboard components and subsystems, with software as a runner-up because of cost and the innate drive to be first to market. However, as the Samsung Note 7 battery failure and subsequent recall has shown, releasing a product with flaws that are later discovered in the field by your customers is a bad idea. Despite this, the hype surrounding IoT is truly at its peak relative to other emerging technologies.

The U.S. has targeted infrastructure as a key focus. The proposed infrastructure buildout combined with growth in U.S. industrial capacity would benefit from incorporation of IIoT sensors and systems. At a Consumer Electronics Show (CES), many companies demonstrated attempts to deploy IIoT in industrial facilities-often with woefully inadequate performance and cybersecurity. The rush to develop and deploy will no doubt increase consumer IoT being used for IIoT, accelerating the IoT and IIoT convergence.

At the U.S. Department of Commerce (DOC) IoT workshop, participants spent a significant amount of time discussing the important role government can play in setting IoT standards. IoT experts at the workshop made it clear that with assistance from the federal government-specifically the U.S. Department of Energy (DOE) and DOC and their national laboratories-guidelines for cybersecure and robust IoT could be developed. With help from the government and organizations such as ISA, industry will have a clearer path to develop industry-centric IIoT rather than rushing to field consumer IoT devices. The question is that, even with this framework, will simple cost and a discount of risk dominate, so that IIoT essentially becomes IoT wrapped in a harder shell? We propose that this is what will occur.

However, we must take heed when it comes to cybersecurity and realize that with commercial IoT, an industrial target could be attacked in a manner similar to an attack on a commercial target-but with very different consequences. The solution? Although we should accept that IoT and IIoT will converge, there must be clear distinctions in cyberarchitecture and associated protections. This goes for implementation as well as regulations and guidelines proposed by governments and industry standards developed by organizations like ISA.

Figure 1. IoT for electric grid

Industrial Internet of Things

Could seemingly trivial items, such as Amazon Echo/Alexa, be worthy of consideration for industrial automation and applications? Many stalwarts of the status quo voice concerns about safety standards and dangers of this technology in the industrial setting. Although these are valid concerns, a more important concern is that commercial IoT standards or best practices do not always apply to IIoT concerns.

IIoT is a specialized IoT implemented in ruggedized packages suitable for industrial application environments. In fact, legacy industrial control devices, such as programmable logic controllers, will be compatible-for the time being-with IIoT running alongside. IIoT benefits from data flowing through standards-based and common networks. From a networking standpoint, the IIoT systems will break the ongoing practice of using proprietary networks and bring into place a common standards-based networking technology. The convergence of IT and operational technology (OT) operation knowledge for industrial automation environments is well underway. Soon IIoT will approach the network edge for almost every industrial application. IIoT installations can include hundreds or even thousands of sensors across a large facility. To handle all of this information, one approach is for IIoT to leverage the cloud in a manner similar to the Alexa example with IoT. In his book Internet of Things with Python, Gaston Hillar illustrates how sensor readings from IoT devices compound into a situation that must be managed.

A typical industrial practice involves acquiring one measurement per second from each IoT device. The number of measurements-from just one device-is:

• 60 measurements for all the variables per minute
• 3,600 (60  x  60) measurements per hour
• 86,400 (3,600 x 24) measurements per day
• 31,536,000 (86,400 x 365) measurements per year (assuming a nonleap year)

Consider the situation where an industrial facility has 3,000 IIoT devices running the same code, thereby generating 94,608,000,000 (31,356,300 x 3,000) measurements per year. (Each IIoT device is generating one reading per second.) In addition, it is envisioned that a data ingestion engine may analyze and acquire information from other data sources, such as tweets about weather-related issues in the locations in which the sensors are capturing data. The net result is huge volumes of both structured and unstructured data to analyze computationally to reveal patterns and associations.

From a convergence standpoint, many of these big data repositories and data manipulation centers will be the same for both IoT and IIoT. The key differences are cost and technical capability, and these commercial repositories are quite capable of servicing IIoT data at a low cost. Comingling of data between a home toaster oven (IoT) and the IIoT data from a cement kiln, for example, is not the real worry. The greater concern is a denial of service attack on the large provider. If we consider Amazon and its Amazon Web Services (AWS) and similar technologies, we can appreciate how an attack on a commercial business such as Amazon could disrupt critical processes supported by IIoT in a factory.

What constitutes IoT and the technology levels associated with IoT use in, for example, the electric grid? Figure 1 illustrates the situation.

Figure 2. Spectrum sensing, sharing, decision, and mobility functional components of an IoT device for dense deployments in industrial settings

Intersecting technologies

With the introduction and promulgation of IoT devices in an industrial setting, a wide range of questions and problems arise, including the following examples:

1. How do wireless IoT devices all share the frequency spectrum? Issues of spectrum congestion-such as numerous devices sharing the same frequency spectrum-are lumped into the general category of the "spectrum crunch." One example of the correct answer can be for the IoT device to incorporate levels of spectrum sensing (in essence acting as a spectrum analyzer for the frequencies of "interest"), while having spectrum mobility (being able to change operating frequencies easily and quickly). The spectrum subsystem elements for such an adaptable IoT device are shown in figure 2.

2. Process control systems speak a wide range of protocols. Should an IIoT device or system speak one or all of these protocols? Or is having a logical system element perform protocol translation sufficient?

3. "IP addressable to the edge," such as most IoT device and system designs, causes the logical element and subsystem design-which is foundational to the vast majority of today's industrial networks-to be incorrect. IP-to-the-edge can provide wonderful integration into IT-centric networks, thereby allowing IT security applications to have entire network visibility. A "flat architecture" provided by IP-to-the-edge allows for an everything-to-everything level of connectivity. It also allows users to partition a variety of working zones based on operational or business needs. We believe the constraints should be set by application and business needs, not by technology incompatibility. This should be one basic concept of IIoT.

4. IoT movement has also advanced sensing technology. IoT edge devices may have varying levels of complexity and functionality, with various vendors leaning toward sophisticated and relatively energy-consumption-intensive operation, whereas others promote the advancing technology of passive wireless sensor tags (with no batteries, extremely low cost, and intrinsically safe operation). The ISA Communications Division has collaborated with the U.S. National Aeronautics and Space Administration, DOE, and other organizations during the past six years to conduct passive wireless sensor tag workshops and promote new types of low-cost wireless sensing technologies for IIoT.

5. In essence, the question distills to the following: What does the industrial network have to look like for IIoT devices to be used? Several great standardization activities have been initiated in IEEE and the Internet Engineering Task Force (IETF), such as IEEE 802.1 Time Sensitive Networking and the IETF Deterministic Networking. Those technologies are created to address the need of IIoT, which allows a single network to share its resources and to be deterministic to reserve network bandwidth for time-critical applications. An initial set of functionality and performance "answers" for IoT devices in a factory automation setting is provided in figure 3.

Figure 3. An industrial Internet-ready, time-sensitive network architecture

1. Communicate outside the plant in standard ways
2. Have object-oriented data models that relate to their physical objects
3. Not interfere with the reliability, integrity, or security of control applications
4. Be portable to devices on the plant floor
5. Share the existing infrastructure
6. Anticipate various forms of wireless media
7. Be able to easily add or reconfigure applications without affecting the existing plant.

Data of "things"

In the preceding section, we introduced the data footprint of IIoT with some simple calculations. In this section, we delve deeper into why IIoT will simply ride alongside or leverage data technology from commercial IoT. Does this affect security in the industrial (IIoT) space? Even if a company does not use the same data storage systems as AWS or other commercial IoT, its software could have many of the same security flaws. For custom applications, such as a factory IIoT system, only small portions of original code are introduced; the rest of the software leverages preexisting objects and modules born in the commercial IoT sector.

Thus, is this wave of data really all the same ocean from a storage and software standpoint? In other words, because of modular programming and reuse, are commercial IoT flaws present in often-unpatched IIoT systems? Once a vulnerability in the commercial space (IoT) is known to the hacker community, hackers can easily develop exploits and payloads that leverage the same vulnerability in unpatched IIoT systems.

Integration of IoT devices into a control system world of supervisory control and data acquisition (SCADA), distributed control systems (DCSs), and industrial control systems (ICSs) will lead to required changes to the decades-old ISA-95 Purdue model or the related ISA-88 factory automation network architecture. Such statements simply follow the facts that IP-addressable devices-such as most, but not all, IoT devices and systems-integrated into network-centric architectures logically lead to a change in the deployment fabric. An illustrative architecture is presented in figure 4. What is most noteworthy of such an IoT architecture-data fabric-is that it follows an IT-centric network architecture, thereby allowing for standard IT cybersecurity tools to be suggested for use.

We are not promoting the network architecture shown in figure 4 as a possible replacement for current SCADA/DCS/ICS architectures. It is provided simply as an illustration of an integrated and collaborative IIoT architecture.

The Industrial Internet Consortium-like many similar groups-has developed a conceptual architecture that presents one "view" of IIoT, shown in figure 5.

Again, where do standards come into play? Maciej Kranz of Cisco states, "The IoT World Forum has been working on a common model to drive interoperability across all IoT components: devices and controllers, networks, edge computing, data storage, applications, and analytics. The IoT World Forum Reference Model organizes these components into layers and provides a graphical representation of IoT and all that it entails." Kranz concludes with this bold statement, "The IoT World Forum Reference Model opens the door to an 'Open IoT' system, with guaranteed interoperability." (Readers who are knowledgeable or who participated in the ISA95 and ISA100 development processes can attest to the difficulty of achieving simply stated goals, such as "guaranteed interoperability.") The reference model is presented in figure 6.

Figure 4. An example of multifunction IoT architecture

Figure 5. An example of conceptual IIoT architecture from the Industrial Internet Consortium
Source: Infosys

Figure 6. An example of conceptual IIoT architecture
Source: IoT World Forum Architecture Committee

Cybersecurity, IoT, and the attack surface

The introduction of IoT devices, in particular IP-addressable devices, into an industrial setting most assuredly increases the number of elements/devices that are vulnerable to cyberattack. The situation was illustrated in the 2016 distributed denial of service (DDoS) cyberattack attributed to IoT devices first being infected with malware, then being coordinated in the DDoS attack on major Internet routers.

Does this warrant avoidance of IoT devices in an industrial setting? As directors and directors-elect of two of ISA's technical divisions, the authors of this paper answer that question with a resounding "no." However, such cybersecurity instances do illustrate the need for a change from the decades-old defense-in-depth ISA-99 (ISA/IEC 62443) model. In a future article, we will present a bold design for a cybersecure network architecture appropriate for 2017 and beyond.

Lower costs, enhanced features, and higher cyberrisks-these are what we can expect as IoT and IIoT converge. Standards and guidelines can help carve an orderly path forward. A path for IoT in industry will be needed, because infrastructure initiatives will likely invite rapid IIoT deployment.

ISA's Communications Division and Test & Measurement Division currently have a joint working group focused on IIoT with the associated examination of functional and operational security if and when IoT devices are deployed into a control system. Although the term "cyber" is often overused, it truly applies in the world of IIoT; however, new sensor and control capabilities bring enhanced attack surfaces in the world of cybersecurity.

In follow-up articles in this series, the authors will discuss cybersecurity implications for our overall critical infrastructure and drones for remote inspection to uphold cybersecurity assurance.

ISA offers standards-based industrial cybersecurity training, certificate programs, conformity assessment programs, and technical resources. Please visit the following ISA links for more information:

• ISA Global Cybersecurity Alliance
• Cybersecurity Resources Portal
• Cybersecurity Training
• IEC 62443 Conformance Certification
• ISA Suite of Security Standards
• ISA Family of Standards
• ISA/IEC 62443 Cybersecurity Certificate Programs

About the Author
Peter Fuhr, PhD, is a distinguished scientist at Oak Ridge National Laboratory and also serves as the technology director for the Unmanned Aerial Systems (UAS) Research Laboratory. He is the director of the ISA Test & Measurement Division.

About the Author
Marissa Morales-Rodriguez, PhD, is a research and development scientist at Oak Ridge National Laboratory. She has been working in the area of chemical sciences, concentrating on applications related to sensing, additive manufacturing, and document security. She is director-elect of the ISA Test & Measurement Division.

About the Author
Sterling Rooke, PhD, is the founder of X8 LLC, a technology company focused on industrial sensors with an eye toward cyber- and energy security. On a part-time basis, Rooke is the director of training within a Cyber Operations Squadron in the U.S. Air Force. In his role as a reserve military officer, Rooke leads airman through training exercises to prepare for future conflicts in cyberspace. He is the director-elect of the ISA Communication Division.

About the Author
Penny Chen, PhD, is a senior principal technology strategist at Yokogawa US Technology Center (USTC), responsible for technology strategy and standardization focusing on wireless, networking, and related security, and exploring new technologies for industrial applications. Chen is actively involved in ISA100, Wireless Systems for Automation, and a variety of IoT standardization activities, including IEEE P2413 IoT Architecture Reference Framework. Chen received a PhD in electrical engineering from Northwestern University. She is the director of the ISA Communications Division.

A version of this article also was published at InTech magazine.