Business development entails tasks and processes to develop and implement growth opportunities within and between organizations. It is a subset of the fields of business, commerce and organizational theory. Business development is the creation of long-term value for an organization from and for customers, markets, and relationships (from https://en.wikipedia.org/wiki/Business_development). Understanding the needs of current and future customers should be the baseline for business development. There are two main dimensions of business development, exploitation of current resources (continuous improvements) and exploration of new value (disruptive business models).
Flexibility in manufacturing means the ability to deal with slightly or greatly mixed parts, to allow variation in parts assembly and variations in process sequence, change the production volume and change the design of certain product being manufactured.
A lead time is the latency between the initiation and execution of a process. For example, the lead time between the placement of an order and delivery of a new car from a manufacturer (from https://en.wikipedia.org/wiki/Lead_time)
In systems engineering, dependability is a measure of a system's availability, reliability, and its maintainability, and maintenance support performance, and, in some cases, other characteristics such as durability, safety and security. In software engineering, dependability is the ability to provide services that can defensibly be trusted within a time-period. This may also encompass mechanisms designed to increase and maintain the dependability of a system or software. (from https://en.wikipedia.org/wiki/Dependability)
In business, engineering, and manufacturing, quality has a pragmatic interpretation as the non-inferiority or superiority of something; it's also defined as being suitable for its intended purpose (fitness for purpose) while satisfying customer expectations. (from https://en.wikipedia.org/wiki/Quality_(business))
Quality assurance (QA) is a way of preventing mistakes and defects in manufactured products and avoiding problems when delivering solutions or services to customers; which ISO 9000 defines as "part of quality management focused on providing confidence that quality requirements will be fulfilled". This defect prevention in quality assurance differs subtly from defect detection and rejection in quality control, and has been referred to as a shift left as it focuses on quality earlier in the process i.e. to the left of a linear process diagram reading left to right. (from https://en.wikipedia.org/wiki/Quality_control)
Productivity describes various measures of the efficiency of production. A productivity measure is expressed as the ratio of output to inputs used in a production process, i.e. output per unit of input. Productivity is a crucial factor in production performance of firms and nations. (from https://en.wikipedia.org/wiki/Productivity)
Optimisation challenges must be faced along the entire supply chain or value network, involving OEMs, components suppliers, service providers and SMEs. The transparency of customer requirements and value within the value chain is an important driver for optimisation.
Material efficiency is a description or metric which expresses the degree in which raw materials are consumed, incorporated, or wasted, as compared to previous measures in construction / manufacturing projects or physical processes. Making a usable item out of thinner stock than a prior version increases the material efficiency of the manufacturing process. (from https://en.wikipedia.org/wiki/Material_efficiency)
Product life extension aims at increasing the value from invested resources, providing a useful life that is as long as possible, and maximizing profitability over the life cycle of assets. It includes activities such as repair, upgrade, and remanufacture as well as Innovative re-use of equipment
Waste minimisation is a set of processes and practices intended to reduce the amount of waste produced. By reducing or eliminating the generation of harmful and persistent wastes, waste minimisation supports efforts to promote a more sustainable society. Waste minimisation involves redesigning products and processes and/or changing societal patterns of consumption and production. (from https://en.wikipedia.org/wiki/Waste_minimisation)
Occupational safety and health (OSH), also commonly referred to as occupational health and safety (OHS), occupational health or workplace health and safety (WHS), is a multidisciplinary field concerned with the safety, health, and welfare of people at work. (from https://en.wikipedia.org/wiki/Occupational_safety_and_health)
The efficiency and sustainability of both the manufacturing of actual and future products is still very much determined by the processes that shape and assemble the components of these products.
Innovative products and advanced materials (including nano-materials) are emerging but are not yet developing to their full advantage since robust manufacturing methods to deliver these products and materials are not developed for large scale. Research is needed to ensure that novel manufacturing processes can efficiently exploit the potential of novel products for a wide range of applications.
Integration of non-conventional technologies (e.g. laser, ultrasonic) towards the development of new multifunctional manufacturing processes (including in process concept: inspection, thermal treatment, stress relieving, machining, joining
In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term "artificial intelligence" is used to describe machines that mimic "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving" (from https://en.wikipedia.org/wiki/Artificial_intelligence)
Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 inclusive. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false (from https://en.wikipedia.org/wiki/Fuzzy_logic)
In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection. (https://en.wikipedia.org/wiki/Genetic_algorithm)
Artificial neural networks (ANN) or connectionist systems are computing systems vaguely inspired by the biological neural networks and astrocytes that constitute animal brains. The neural network itself is not an algorithm, but rather a framework for many different machine learning algorithms to work together and process complex data inputs. Such systems "learn" to perform tasks by considering examples, generally without being programmed with any task-specific rules. (from https://en.wikipedia.org/wiki/Artificial_neural_network)
Data acquisition is the process of sampling signals that measure real world physical conditions and converting the resulting samples into digital numeric values that can be manipulated by a computer. Data acquisition systems, abbreviated by the acronyms DAS or DAQ, typically convert analog waveforms into digital values for processing. The components of data acquisition systems include:
Sensors, to convert physical parameters to electrical signals.
Signal conditioning circuitry, to convert sensor signals into a form that can be converted to digital values.
Analog-to-digital converters, to convert conditioned sensor signals to digital values.
Data acquisition applications are usually controlled by software programs developed using various general purpose programming languages
So, as a summary, Data acquisition is in itself a vast group of protocols, technologies, sensors, hardware and software…
Cloud computing can be deployed as private cloud, public cloud, hybrid cloud
Digital Manufacturing Platforms can be ran into IaaS, PaaS or SaaS.
Considerations need to be made to security measures in the cloud (kubernetes, container security), identity & access, or carefully considering the security measures by the respective cloud services providers.
Data storage is the recording (storing) of information (data) in a storage medium. DNA and RNA, handwriting, phonographic recording, magnetic tape, and optical discs are all examples of storage media. (from https://en.wikipedia.org/wiki/Database)
Dataspaces are an abstraction in data management that aim to overcome some of the problems encountered in data integration system. The aim is to reduce the effort required to set up a data integration system by relying on existing matching and mapping generation techniques, and to improve the system in "pay-as-you-go" fashion as it is used. (From https://en.wikipedia.org/wiki/Dataspaces)
Advanced machine interaction with humans through ubiquity of mobile devices will enable users to receive relevant production and enterprise-specific information regardless of their geographical location and tailored to the context and the skills/responsibilities they own. Interactions with ICT infrastructures and equipment will be natural language-like
The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. (from https://en.wikipedia.org/wiki/Internet_of_things)
The Cygnus Generic Enabler brings the means for managing the history of context that is created as a stream of data which can be injected into multiple data sinks, including some popular databases like PostgreSQL, MySQL, MongoDB or AWS DynamoDB as well as BigData platforms like Hadoop, Storm, Spark or Flink.
The Orion Context Broker Generic Enabler is the core and mandatory component of any “Powered by FIWARE” platform or solution. It enables to manage context information in a highly decentralized and large-scale manner. It provides the FIWARE NGSIv2 API which is a simple yet powerful Restful API enabling to perform updates, queries or subscribe to changes on context information.
Simulation (often referred to as digital twins) is the imitation of the operation of a real-world process or system. The act of simulating something first requires that a model be developed; this model represents the key characteristics, behaviors and functions of the selected physical or abstract system or process. The model represents the system itself, whereas the simulation represents the operation of the system over time. (from https://en.wikipedia.org/wiki/Simulation)
Mechatronics, which is also called mechatronic engineering, is a multidisciplinary branch of engineering that focuses on the engineering of both electrical and mechanical systems, and also includes a combination of robotics, electronics, computer, telecommunications, systems, control, and product engineering. (From https://en.wikipedia.org/wiki/Mechatronics)
Production equipment does not yet take full advantage of the benefits that new and advanced materials offer, and factories of the future will need more advanced equipment to meet the requirements for energy efficiency and environmental targets and to meet new demands for a connected world. The future will therefore see modern, lightweight, long-lasting/flexible and smart equipment able to produce current and future products for existing and new markets. There will be a step change in the construction of such equipment, leading to a sustainable manufacturing base able to deliver high added value products and customised production. Increased smartness in the manufacturing equipment also enables a systems approach with machines able to learn from each other and impacting on the human-machine interface.
Smarter equipment and manufacturing systems with self-diagnosis (temperature, vibrations, noise) and embedded sensing, memory or active architecture, with functional materials allowing them to adjust work processes and operations to variances in structure, shape and material composition (right first time manufacture).. Capture of machine data through this inherent ‘smartness’ for communication between machines (for M2M), at factory level and through supply chains for a systems approach to manufacturing and meeting customer demand.
New equipment components taking advantage of new designs and advanced materials (e.g. gears and transmissions providing longer lifetime of equipment, active surfaces that can embed and release lubricant when needed (higher pressures or temperatures))
Continuous monitoring of the condition and performance of the manufacturing system on component and machine level, enables sustainable and competive manufacturing, also by introducing autonomous diagnosis capabilities and context-awareness. Detecting, measuring and monitoring the variables, events and situations will increase the performance and reliability of manufacturing systems. This involves advanced metrology, calibration and sensing, signal processing and model-based virtual sensing for a wide range of applications, e.g. event pattern detection, diagnostics, anomaly detection, prognostics and predictive maintenance.
Control technologies will be further exploiting the increasing computational power and intelligence in order to come forward to the demands of increased speed and precision in manufacturing. Advanced control strategies will allow the use of lighter actuators and structural elements for obtaining very rigid and accurate solutions, replacing slower and more energy-intensive approaches. Learning controllers adapt the behaviour of systems to changing environments or system degradation, taking into account constraints and considering alternatives, hereby relying on robust industrial real-time communication technologies, system modelling approaches and distributed intelligence architectures.
Intelligent components enable the deployment of safe, energy-efficient, accurate and flexible or reconfigurable products and production systems. This includes the introduction of smart actuators and the use of advanced end-effectors composed of passive and active materials. Energy technologies are gaining importance, such as (super)capacitors, pneumatic storage devices, batteries and energy harvesting technologies.
The European Factories of the Future are expected to provide global manufacturing competitiveness, but also to create a large amount of work opportunities for the European population. Future factory workers are therefore key resources for industrial competitiveness as well as important consumers. However, as previously stated, the changing demographics and high skill requirements faced by European industry pose new challenges. Workers with high knowledge and skills (“knowledge workers”) will be scarce resources. Research efforts within Horizon 2020 must address ways to increase the number of people available for, and interested in, manufacturing tasks. This includes the following important aspects of the human resources: - New technology-based approaches to accommodate age-related limitations, through ICT and automation - New technical, educational, and organisational ways to increase the attractiveness of factory work to the young potential workforce, the existing workforce, the potential immigrant workforce, and the older workforce - New approaches to skill- and competence development, as well as skill and knowledge management, to increase competitiveness and be part of the global knowledge society - New ways to organise and compensate factory knowledge workers - New factory human-centric work-environments based on safety and comfort - Ways to integrate future factory work in global and local societal agendas and social patterns
This is a collection of Industrial CyberSecurity Standards and de-facto standards relevant for organizations designing, developing, selecting, installing and operating digital manufacturing platforms. The selection was made on the basis of expert advisory and selections by researchers in their assessment of relevant State of the Art. Next to the standards, readers should also consider the works ongoing in standardisation efforts.
An industry-accepted way to document what security controls exist in IaaS, PaaS, and SaaS services, providing security control transparency. It provides a set of Yes/No questions a cloud consumer and cloud auditor may wish to ask of a cloud provider to ascertain their compliance to the Cloud Controls Matrix (CCM).
It helps cloud service providers and their customers to gauge the security posture and determine if their cloud services are suitably secure. In addition to improving the clarity and accuracy, it also supports better auditability of the CCM controls.
The Industrial Internet Security Framework (IISF) is a cross-industry-focused security framework comprising expert vision, experience and security best practices. It reflects thousands of hours of knowledge and experiences from security experts, collected, researched and evaluated for the benefit of all IIoT system deployments.
It builds on the ‘Industrial Internet of Things Reference Architecture’ (IIRA), that lays out the most important architecture components, how they fit together and how they influence each other. Each of these components must be made secure, as must the key system characteristics that bind them together into a trustworthy system.
It reviews security assessment for organizations, architectures and technologies. It outlines how to evaluate attacks as part of a risk analysis and highlights the many factors that should be considered, ranging from the endpoints and communications to management systems and the supply chains of the elements comprising the system. Different roles are identified that should be considered in conjunction with the key characteristics, including, owner/operator, system integrator/builder and equipment vendor. Each role offers different risk management perspectives that affect the decisions regarding security and privacy.
NAMUR, the "User Association of Automation Technology in Process Industries", is an international association of user companies (established in 1949) and represents their interests concerning automation technology. NAMUR numbers over 150 member companies. The achievement of added value through automation engineering is at the forefront in all NAMUR member company activities. NAMUR conducts a frank and fair dialogue with manufacturers.
NAMUR’s Automation Security working group 4.18 addresses issues including the following topics in the context of its experience exchange, its concept developments, formulation of requirements to be met by automation solutions and its involvement in national and international standardisation.
Relevant recommendations and worksheets
NA 163 Security Risk Assessment of SIS (Safety Instrumented Systems)
NA 169 Automation Security Management in the Process Industry. NA 169 describes the steps to systematically build a Cyber Security Management System (CSMS) for automation systems in the process industry in order to ensure the correct operation of the functional safety devices, to protect critical data and to ensure the availability and reliability of the plants
The overall concept is the use of the Admnistrative Asset Shell (AAS). It is requesting access to an object. In the context of an AAS an object typically is a submodel or a property or any other submodel element connected to the asset. The implemented access control mechanism of the AAS evaluates the access permission rules (2a) that include constraints that need to be fulfilled w.r.t. the subject attributes (2b), the object attributes and the environment conditions (2d). The focus is on access control. An object in the context of ABAC corresponds typically to a submodel or to a submodel element. The object attributes again are modelled as submodel elements. Subject Attributes need to be accessed either via an external policy information point or they are defined as properties within a special submodel of the AAS. A typical subject attribute is its role. The role is the only subject attribute defined in case of role based access control. Optionally, environment conditions can be defined. In role based access control no environment conditions are defined. Environment conditions can be expressed via formula constraints. To be able to do so the values needed should be defined as property or reference to data within a submodel of the AAS.
Development of standards for cybersecurity and data protection covering all aspects of the evolving information society including but not limited to: - Management systems, frameworks, methodologies - Data protection and privacy - Services and products evaluation standards suitable for security assessment for large companies and small and medium enterprises (SMEs) - Competence requirements for cybersecurity and data protection - Security requirements, services, techniques and guidelines for ICT systems, services, networks and devices, including smart objects and distributed computing devices Included in the scope is the identification and possible adoption of documents already published or under development by ISO/IEC JTC 1and other SDOs and international bodies such as ISO, IEC, ITU-T, and industrial fora. Where not being developed by other SDO's, the development of cybersecurity and data protection CEN/CENELEC publications for safeguarding information such as organizational frameworks, management systems, techniques, guidelines, and products and services, including those in support of the EU Digital Single Market.
Its scope is to contribute, support and coordinate the preparation of international standards for systems and elements used for industrial process measurement, control and automation at CENELEC level. To coordinate standardisation activities which affect integration of components and functions into such systems including safety and security aspects. This CENELEC work of standardisation is to be carried out for equipment and systems and closely coordinated with IEC TC65 and its subcommittees with the objective of avoiding any duplication of work while honouring standing agreements between CENELEC and IEC.
While oriented in the first place to consumer devices, ETSI EN 303 645, a standard for cybersecurity in the Internet of Things is relevant for manufacturing considerations. The standard establishes a security baseline for internet-connected consumer products and provides a basis for future IoT certification schemes. Based on the ETSI specification TS 103 645, EN 303 645 went through National Standards Organization comments and voting, engaging even more stakeholders in its development and ultimately strengthening the resulting standard. The EN is a result of collaboration and expertise from industry, academics and government.
ETSI EN 303 645 specifies 13 provisions for the security of Internet-connected consumer devices and their associated services. IoT products in scope include connected children’s toys and baby monitors, connected safety-relevant products such as smoke detectors and door locks, smart cameras, TVs and speakers, wearable health trackers, connected home automation and alarm systems, connected appliances (e.g. washing machines, fridges) and smart home assistants. The EN also includes 5 specific data protection provisions for consumer IoT.
The Smart Applications REFerence (SAREF) ontology is a shared model of consensus that facilitates the matching of existing assets in the smart applications domain. SAREF provides building blocks that allow separation and recombination of different parts of the ontology depending on specific needs.
SAREF4INMA, an extension of SAREF that was created for the industry and manufacturing domain. SAREF4INMA was created to be aligned with related initiatives in the smart industry and manufacturing domain in terms of modelling and standardization, such as the Reference Architecture Model for Industry 4.0 (RAMI), which combines several standards used by the various national initiatives in Europe that support digitalization in manufacturing.
These initiatives include, but are not limited to, the platform Industrie 4.0 in Germany, the Smart Industry initiative in the Netherlands, Industria 4.0 in Italy, the 'Industrie du future initiative' in France and more.
It extends SAREF with 24 classes (in addition to a number of classes directly reused from the SAREF ontology and the SAREF4BLDG extension), 20 object properties (in addition to a number of object properties reused from the SAREF ontology and the SAREF4BLDG extension) and 11 data type properties. SAREF4INMA focuses on extending SAREF for the industry and manufacturing domain to solve the lack of interoperability between various types of production equipment that produce items in a factory and, once outside the factory, between different organizations in the value chain to uniquely track back the produced items to the corresponding production equipment, batches, material and precise time in which they were manufactured.
This document provides guidance on how to secure Industrial Control Systems (ICS), including Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and other control system configurations such as Programmable Logic Controllers (PLC), while addressing their unique performance, reliability, and safety requirements. 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.
ICS cybersecurity programs should always be part of broader ICS safety and reliability programs at both industrial sites and enterprise cybersecurity programs, because cybersecurity is essential to the safe and reliable operation of modern industrial processes. Threats to control systems can come from numerous sources, including hostile governments, terrorist groups, disgruntled employees, malicious intruders, complexities, accidents, and natural disasters as well as malicious or accidental actions by insiders. ICS security objectives typically follow the priority of availability and integrity, followed by confidentiality.
The Framework focuses on using business drivers to guide cybersecurity activities and considering cybersecurity risks as part of the organization’s risk management processes. The Framework consists of three parts: the Framework Core, the Implementation Tiers, and the Framework Profiles. The Framework Core is a set of cybersecurity activities, outcomes, and informative references that are common across sectors and critical infrastructure. Elements of the Core provide detailed guidance for developing individual organizational Profiles. Through use of Profiles, the Framework will help an organization to align and prioritize its cybersecurity activities with its business/mission requirements, risk tolerances, and resources. The Tiers provide a mechanism for organizations to view and understand the characteristics of their approach to managing cybersecurity risk, which will help in prioritizing and achieving cybersecurity objectives.
While this document was developed to improve cybersecurity risk management in critical infrastructure, the Framework can be used by organizations in any sector or community. The Framework enables organizations – regardless of size, degree of cybersecurity risk, or cybersecurity sophistication – to apply the principles and best practices of risk management to improving security and resilience.
The Framework provides a common organizing structure for multiple approaches to cybersecurity by assembling standards, guidelines, and practices that are working effectively today.
The Cybersecurity Framework (CSF) Version 1.1 implementation details developed for the manufacturing environment. The “Manufacturing Profile” of the CSF 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.
Internet of Things (IoT) devices often lack device cybersecurity capabilities their customers organizations and individuals—can use to help mitigate their cybersecurity risks. Manufacturers can help their customers by improving how securable the IoT devices they make are by providing necessary cybersecurity functionality and by providing customers with the cybersecurity-related information they need. This publication describes recommended activities related to cybersecurity that manufacturers should consider performing before their IoT devices are sold to customers. These foundational cybersecurity activities can help manufacturers lessen the cybersecurity-related efforts needed by customers, which in turn can reduce the prevalence and severity of IoT device compromises and the attacks performed using compromised devices
The following is a collection of Industrial CyberSecurity Standards and de-facto standards relevant for organizations designing, developing, selecting, installing and operating digital manufacturing platforms. The selection was made on the basis of expert advisory and selections by researchers in their assessment of relevant State of the Art. Next to the standards, readers should also consider the works ongoing in standardization efforts
The CIS Controls™ are a prioritized set of actions that collectively form a defense-in-depth set of best practices that mitigate the most common attacks against systems and networks. The CIS Controls are developed by a community of IT experts who apply their first-hand experience as cyber defenders to create these globally accepted security best practices. The experts who develop the CIS Controls come from a wide range of sectors including, retail, manufacturing, healthcare, education, government, defense, and others. So, while the CIS Controls address the general practices that most organizations should take to secure their systems, some operational environments may present unique requirements not addressed by the CIS Controls.
The guidance on how to apply the security best practices found in CIS Controls. For each top-level CIS Control, there is a brief discussion of how to interpret and apply the CIS Control in such environments, along with any unique considerations or differences from common IT environments. The applicability or not of specific Sub-Controls is addressed and additional steps needed in ICS environments are explained.
The ISA/IEC 62443 standard specifies security capabilities for (industrial) control system components. Developed by the ISA99 committee and adopted by the International Electrotechnical Commission (IEC), provides a framework to address and mitigate security vulnerabilities in industrial automation and control systems (IACSs). it is based upon the input and knowledge of IACS security experts from across the globe to develop consensus standards that are applicable to all industry sectors and critical infrastructure. Central is the application of IACS security zones and conduits (isolation & segmentation), which were introduced in 62443-1-1,
ISA-62443-4-2, Security for Industrial Automation and Control Systems: Technical Security Requirements for IACS Components, provides the cybersecurity technical requirements for components that make up an IACS, specifically the embedded devices, network components, host components, and software applications.
Based on the IACS system security requirements of ISA/IEC 62443‑3-3, System Security Requirements and Security Levels, 4-2 specifies security capabilities that enable a component to mitigate threats for a given security level without the assistance of compensating countermeasures.
ISA/IEC 62443-4-1, Product Security Development Life-Cycle Requirements, specifies process requirements for the secure development of products used in an IACS and defines a secure development life cycle for developing and maintaining secure products. The life cycle includes security requirements definition, secure design, secure implementation (including coding guidelines), verification and validation, defect management, patch management, and product end of life.
ISA/IEC 62443-3-2, Security Risk Assessment, System Partitioning and Security Levels, is based on the understanding that IACS security is a matter of risk management. 3-2 will define a set of engineering measures to guide organizations through the process of assessing the risk of a particular IACS and identifying and applying security countermeasures to reduce that risk to tolerable levels.
By aligning the identified target security level with the required security level capabilities 3‑3, System Security Requirements and Security Levels it takes the earlier 1-1 standard a step further. 2-3, Patch Management in the IACS Environment addresses the installation of patches, also called software updates, software upgrades, firmware upgrades, service packs, hot fixes, basic input/output system updates, and other digital electronic program updates that resolve bug fixes, operability, reliability, and cybersecurity vulnerabilities. It covers many of the problems and industry concerns associated with IACS patch management for asset owners and IACS product suppliers. It also describes the effects poor patch management can have on the reliability and operability of an IACS.
ISO 27000 (or ISO27k) refers to a standard and a series of international standards (27001, 27002, ...) set up by the ISO (International Standards Organization) on information security management series (ISMS). The standard was initiated around 2005 and revised multiple times (2016, 2018) with the support of the different ISO member states representatives, people with an information security background and profession.
The standard describes a norm to which organizations can organize themselves in order to properly manage information and information security. It sets out a series policies, defines the setup of a system to control and manage the policies. Today the standard is being referred to by many compliancy requirement regulations and setups such as the Network and Information Security Directive by the European Commission and the European Member States.
The ISO 27000 series have been divised into multiple sub-standards
27001 :This is the specification for an information security management system (an ISMS) which replaced the old BS7799-2 standard
27002 : This is the 27000 series standard number of what was originally the ISO 17799 standard (which itself was formerly known as BS7799-1)
27003 : guidance for the implementation of an ISMS (IS Management System)
27004 : measurement and metrics
27005 : methodology independent ISO standard
27006 : accreditation of organizations offering ISMS certification.
27007 : ISMS auditing
27032 : CyberSecurity
27033 : Network Security
(* 27013 : Manufacturing)
The objective of the 27001 standard itself is to "provide requirements for establishing, implementing, maintaining and continuously improving an Information Security Management System (ISMS)". Regarding its adoption, this should be a strategic decision. Further, "The design and implementation of an organization's information security management system is influenced by the organization's needs and objectives, security requirements, the organizational processes used and the size and structure of the organization". The original standard was more oriented towards planning and organizing, the later versions more towards measuring and evaluating. 27002 is about controls and control mechanisms.
Organizations can have their ISMS's or their ISO process certified, which can be needed for compliance reasons.
Provides guidance based on ISO/IEC 27002:2013 applied to process control systems used by the energy utility industry for controlling and monitoring the production or generation, transmission, storage and distribution of electric power, gas, oil and heat, and for the control of associated supporting processes.
central and distributed process control, monitoring and automation technology as well as information systems used for their operation, such as programming and parameterization devices;
digital controllers and automation components such as control and field devices or Programmable Logic Controllers (PLCs), including digital sensor and actuator elements;
all further supporting information systems used in the process control domain, e.g. for supplementary data visualization tasks and for controlling, monitoring, data archiving, historian logging, reporting and documentation purposes;
communication technology used in the process control domain, e.g. networks, telemetry, telecontrol applications and remote control technology;
Advanced Metering Infrastructure (AMI) components, e.g. smart meters;
measurement devices, e.g. for emission values; - digital protection and safety systems, e.g. protection relays, safety PLCs, emergency governor mechanisms;
energy management systems, e.g. of Distributed Energy Resources (DER), electric charging infrastructures,
all software, firmware and applications installed on above-mentioned systems, e.g. DMS (Distribution Management System) applications or OMS (Outage Management System); - any premises housing the above-mentioned equipment and systems;
remote maintenance systems for above-mentioned systems.
ISO/IEC 27019:2017 does not apply to the process control domain of nuclear facilities. This domain is covered by IEC 62645. ISO/IEC 27019:2017 also includes a requirement to adapt the risk assessment and treatment processes described in ISO/IEC 27001:2013 to the energy utility industry-sector?specific guidance provided in this document.