This document provides guidance on how to secure operational technology (OT) while addressing their unique performance, reliability, and safety requirements. OT encompasses a broad range of programmable systems and devices that interact with the physical environment (or manage devices that interact with the physical environment). These systems and devices detect or cause a direct change through the monitoring and/or control of devices, processes, and events. Examples include industrial control systems, building automation systems, transportation systems, physical access control systems, physical environment monitoring systems, and physical environment measurement systems. The document provides an overview of OT and typical system topologies, identifies common threats and vulnerabilities to these systems, and provides recommended security countermeasures to mitigate the associated risks.

As supply chains become more complex and the origins of products become harder to discern, efforts are emerging that improve traceability of goods by exchanging traceability data records using blockchain and related technologies. This NIST NCCoE publication explores the issues that surround traceability, the role that blockchain and related technologies may be able to play to improve traceability, and several case studies in use today.

Today's manufacturing organizations rely on industrial control systems (ICS) to conduct their operations. Increasingly, ICS are facing more frequent, sophisticated cyber attacks making manufacturing the second-most-targeted industry. Cyber attacks against ICS threaten operations and worker safety, resulting in financial loss and harm to the organization's reputation. The architecture and solutions presented in this guide are built upon standards-based, commercially available products, and represent some of the possible solutions. The solutions implement standard cybersecurity capabilities such as behavioral anomaly detection (BAD), application allowlisting (AAL), file integrity-checking, change control management, and user authentication and authorization. The solution was tested in two distinct lab settings: a discrete manufacturing workcell, which represents an assembly line production, and a continuous process control system (PCS), which represents chemical manufacturing industries. An organization that is interested in protecting the integrity of a manufacturing system and information from destructive malware, insider threats, and unauthorized software should first conduct a risk assessment and determine the appropriate security capabilities required to mitigate those risks. Once the security capabilities are identified, the sample architecture and solution presented in this document may be used.

The last decade has seen an influx of digital connectivity, operation automation, and remote sensing and control mechanisms in the railway domain. The management of the railway operations through the use of distributed sensors and controllers and with programmable and remotely controllable railway signals and switches has led to gains in system efficiency as well as operational flexibility. However, the network connectivity has opened up the railway cyber communication networks to cyber-attacks. These are a class of cyber-physical systems (CPS) with interconnected physical, computational, and communication components. The cyber-attacks on these systems could potentially cascade through these inter-connection and result into significant damage. These systems are safety-critical owing to their large-scale monetary and, more importantly, human life safety concerns. Therefore, it is better to incorporate security and resilience requirements right from the design time. In this paper, we describe a domain-specific framework for simulations in the railway domain. The framework allows analyzing the resilience of railway operations in the presence of cyber-attacks. In particular, our simulation framework allows modeling the railway network as well as the railway transportation. It provides an online graphical modeling environment that allows multiple users to collaborate, through a web-based interface, over the same model for the railway infrastructure as well as network attacks. The framework also allows the user to configure and run experiments through the web-interface and also to visualize the key operational metrics from the railway domain as the experiment is running. The framework also supports executing large simulations in the cloud. In addition, it supports hardware-in-the-loop (HIL) simulation for incorporating physical effects and network attacks that can only be realized realistically in the hardware. A detailed case study is provided to demonstrate the framework's capabilities.

In the past couple of years, railway infrastructure has been growing more connected, resembling more of a traditional Cyber-Physical System [1] model. Due to the tightly coupled nature between the cyber and physical domains, new attack vectors are emerging that create an avenue for remote hijacking of system components not designed to withstand such attacks. As such, best practice cybersecurity techniques need to be put in place to ensure the safety and resiliency of future railway designs, as well as infrastructure already in the field. However, traditional large-scale experimental evaluation that involves evaluating a large set of variables by running a design of experiments (DOE) may not always be practical and might not provide conclusive results [2]. In addition, to achieve scalable experimentation, the modeling abstractions, simulation configurations, and experiment scenarios must be designed according to the analysis goals of the evaluations. Thus, it is useful to target a set of key operational metrics for evaluation and configure and extend the traditional DOE methods using these metrics. In this work, we present a metrics-driven evaluation approach for evaluating the security and resilience of railway critical infrastructure using a distributed simulation framework. A case study with experiment results is provided that demonstrates the capabilities of our testbed.

Cyber-Physical Systems (CPS) consist of embedded computers with sensing and actuation capability, and are integrated into and tightly coupled with a physical system. Because the physical and cyber components of the system are tightly coupled, cyber-security is important for ensuring the system functions properly and safely. However, the effects of a cyberattack on the whole system may be difficult to determine, analyze, and therefore detect and mitigate. This work presents a model based software development framework integrated with a hardware-in-the-loop (HIL) testbed for rapidly deploying CPS attack experiments. The framework provides the ability to emulate low level attacks and obtain platform specific performance measurements that are difficult to obtain in a traditional simulation environment. The framework improves the cybersecurity design process which can become more informed and customized to the production environment of a CPS. The developed framework is illustrated with a case study of a railway transportation system.

This document provides the Cybersecurity Framework (CSF) implementation details developed for the manufacturing environment.The "Manufacturing Profile" of the Cybersecurity Framework can be used as a roadmap for reducing cybersecurity risk for manufacturers that is aligned with manufacturing sector goals and industry best practices.This Manufacturing Profile provides a voluntary, risk-based approach for managing cybersecurity activities and reducing cyber risk to manufacturing systems.The Manufacturing Profile is meant to enhance but not replace current cybersecurity standards and industry guidelines that the manufacturer is embracing.

Industrial control systems (ICS) are composed of sensors, actuators, control processing units, and communication devices all interconnected to provide monitoring and control capabilities. Due to the integral role of the networking infrastructure, such systems are vulnerable to cyber attacks. Indepth consideration of security and resilience and their effects to system performance are very important. This paper focuses on railway control systems (RCS), an important and potentially vulnerable class of ICS, and presents a simulation integration platform that enables (1) Modeling and simulation including realistic models of cyber and physical components and their interactions, as well as operational scenarios that can be used for evaluations of cybersecurity risks and mitigation measures and (2) Evaluation of performance impact and security assessment of mitigation mechanisms focusing on authentication mechanisms and firewalls. The approach is demonstrated using simulation results from a realistic RCS case study.

Cyber-Physical Systems (CPS) are systems with seamless integration of physical, computational and networking components. These systems can potentially have an impact on the physical components, hence it is critical to safeguard them against a wide range of attacks. In this paper, it is argued that an effective approach to achieve this goal is to systematically identify the potential threats at the design phase of building such systems, commonly achieved via threat modeling. In this context, a tool to perform systematic analysis of threat modeling for CPS is proposed. A real-world wireless railway temperature monitoring system is used as a case study to validate the proposed approach. The threats identified in the system are subsequently mitigated using National Institute of Standards and Technology (NIST) standards.

3541 et seq., Public Law (P.L.) 113-283.NIST is responsible for developing information security standards and guidelines, including minimum requirements for federal information systems, but such standards and guidelines shall not apply to national security systems without the express

The National Institute of Standards and Technology (NIST) is developing a cybersecurity testbed for industrial control systems (ICS). The goal of this testbed is to measure the performance of an ICS when instrumented with cybersecurity protections in accordance with practices prescribed by prevailing standards and guidelines. This paper outlines the testbed design and lists research goals, use cases, and performance metrics currently being considered. The paper is also intended to initiate discussion between control and security practitioners – two groups that have had little interaction in the past. Research outcomes from the testbed will highlight specific cases where security technologies impact control performance, as well as motivate methods by which control engineers can leverage security engineering to design control algorithms that extend safety and fault tolerance to include advanced persistent threats.

This paper provides a novel approach in bridging the traditional semantic web based on the HTTP protocol and peer-to-peer-like sensor networks based on the XMPP protocol, thus extending the reach of semantic technologies to private spheres otherwise not accessible due to firewalls and other security measures, but still maintaining a high level of security and end-user data privacy and access control. Index Terms — Internet of Things, Peer-to-peer networks, Semantic web, data privacy, access control, plug computing, grid computing.

This article examines the impact of cybersecurity on the performance of industrial control systems (ICS). Control systems are embedded in essentially all engineered systems, such as our cars, homes, offices, industrial plants, and in critical infrastructures such as power plants, water treatment plants, and transportation systems. To ensure the security of ICS, particularly for critical infrastructures, standards are being developed to ensure ICS cybersecurity. The NIST ICS cybersecurity testbed will be constructed to facilitate the measurement of industrial process performance for systems instrumented with cybersecurity technologies. This testbed will allow for validation of existing security standards and guidelines and will allow researchers to provide valuable feedback to the community on methods, practices, and pitfalls when applying a cybersecurity program to an ICS. Additional work will be required to identify new use cases and pertinent performance metrics. The testbed will provide an opportunity for collaboration between government, research institutions, and industry partners. Interested parties are encouraged to contact the authors directly to discuss opportunities for collaboration.

The purpose of this document is to provide guidance for securing industrial control systems (ICS), including supervisory control and data acquisition (SCADA) systems, distributed control systems (DCS), and other systems performing control functions. The document provides an overview of ICS and typical system topologies, identifies typical threats and vulnerabilities to these systems, and provides recommended security countermeasures to mitigate the associated risks. Because there are many different types of ICS with varying levels of potential risk and impact, the document provides a list of many different methods and techniques for securing ICS. The document should not be used purely as a checklist to secure a specific system. Readers are encouraged to perform a risk-based assessment on their systems and to tailor the recommended guidelines and solutions to meet their specific security, business and operational requirements.The scope of this document includes ICS that are typically used in the electric, water and wastewater, oil and natural gas, chemical, pharmaceutical, pulp and paper, food and beverage, and discrete manufacturing (automotive, aerospace, and durable goods) industries.

Critical infrastructure cyber security solutions for industrial control systems are touted by the sellers as standards-based and comprehensive. Buyer beware, most of these claims are highly exaggerated. Only the International Society for Automation (ISA) is developing standards that are comprehensive in the sense that cyber security requirements control systems are defined as an extension of the security policies for the enterprise. Furthermore, these ISA standards include requirements that account for the dynamics induced by human behavior and the constraints imposed by external interfaces that are not directly controlled by the enterprise owner. This paper describes the seven foundational requirements codified in ISA-99.01-01 and the derived system requirements and metrics. The paper concludes with example security metrics recommended to verify the quality of cyber solutions offered.