Research Outputs
Self-Adaptation Applied to MQTT via a Generic Autonomic Management Framework
Manufacturing enterprises are constantly exploring new ways to improve their own production processes to address the increasing demand of customized production. However, such enterprises show a low degree of flexibility, which mainly results from the need to configure new production equipment at design and run time. In this paper we propose self-adaptation as an approach to improve data transmission flexibility in Industry 4.0 environments. We implement an autonomic manager using a generic autonomic management framework, which applies the most appropriate data transmission configuration based on security and business process related requirements, such as performance. The experimental evaluation is carried out in a MQTT infrastructure and the results show that using self-adaptation can significantly improve the trade-off between security and performance. We then propose to integrate anomaly detection methods as a solution to support self-adaptation by monitoring and learning the normal behavior of an industrial system and show how this can be used by the generic autonomic management framework.
Connected cars — Threats, vulnerabilities and their impact
The growing demand for interoperability between system components within a connected car has led to new security challenges in automotive development. The existing components, based on established technology, are often being combined to form such a connected car. For such established technologies, individual, often sector specific threat and vulnerability catalogs exist. The aim of this paper is to identify blocks of established technologies in a connected car and to consolidate the corresponding threat and vulnerability catalogs relevant for the individual constituent components. These findings are used to estimate the impact on specific system components and subsystems to identify the most crucial components and threats.
Generic Autonomic Management as a Service in a SOA-based Framework for Industry 4.0
Cyber-physical production systems are engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components. In order to make these systems interoperable with each other for addressing Industry 4.0 applications a number of service-oriented architecture frameworks are developed. Such frameworks are composed by a number of services, which are inherently dynamic by nature and thus imply the need for self-adaptation. In this paper we propose generic autonomic management as a service and show how it can be integrated in the Arrowhead framework. We propose generic and reusable interfaces for each phase of the autonomic control loop in order to increase the usability of the service for other frameworks and application systems, while reducing the software engineering effort. To show the utility of our approach in the Arrowhead framework we use a climate control application as a representative example.
Security standard compliance and continuous verification for Industrial Internet of Things
Due to globalization and digitalization of industrial systems, standard compliance is gaining more attention. In order to stay competitive and remain in business, different sectors within industry are required to comply with multiple regulations. Compliance aims to fulfill regulations by including all measures imposed by laws and standards. Every device, application, or service implements several technologies at many levels, and standards support interoperability across them. They help to create global markets for industries and enable networked development in order to be successful and sustainable. This work highlights the importance of standard compliance and continuous verification in industrial Internet of Things and implements an automatic monitoring and standard compliance verification framework. In this work, we focus on security, safety, and organizational aspects of industrial Internet of Things. We identify a number of standards and best practice guidelines, which are used to extract security, safety, and organizational measurable indicator points. In addition, a metric model is provided that forms the basis for the necessary information needed for compliance verification, including requirements, standards, and metrics. Also, we present the prototype of the monitoring and standard compliance verification framework used to show the security compliance of an industrial Internet of Things use case.
Monitoring Industry 4.0 Applications for Security and Safety Standard Compliance
In Industry 4.0 independent entities shall inter-operate to allow flexible and customized production. To assure the parties that individual components are secured to inter-operate, we investigate automated standard compliance. The standard compliance is defined based on given sets of security and safety requirements from which are derived measurable indicator points. Those reflect configurations of systems recommended by security, safety or legally relevant standards and guidelines, which help to demonstrate the state of compliance. We propose in this paper an initial approach to automate such assessment when components are inter-operating with each other by using a monitoring and standard compliance verification framework. This will assure the parties that services or devices within their organizations operate in a secure and standard compliant way, without compromising the underlying infrastructure.
Establishing a Chain of Trust in a Sporadically Connected Cyber-Physical System
Drone based applications have progressed significantly in recent years across many industries, including agriculture. This paper proposes a sporadically connected cyber-physical system for assisting winemakers and minimizing the travel time to remote and poorly connected infrastructures. A set of representative diseases and conditions, which will be monitored by land-bound sensors in combination with multispectral images, is identified. To collect accurate data, a trustworthy and secured communication of the drone with the sensors and the base station should be established. We propose to use an Internet of Things framework for establishing a chain of trust by securely onboarding drones, sensors and base station, and providing self-adaptation support for the use case. Furthermore, we perform a security analysis of the use case for identifying potential threats and security controls that should be in place for mitigating them.
Towards trustworthy end-to-end communication in industry 4.0
Industry 4.0 considers integration of IT and control systems with physical objects, software, sensors and connectivity in order to optimize manufacturing processes. It provides advanced functionalities in control and communication for an infrastructure that handles multiple tasks in various locations automatically. Automatic actions require information from trustworthy sources. Thus, this work is focused on how to ensure trustworthy communication from the edge devices to the backend infrastructure. We derive a meta-model based on RAMI 4.0, which is used to describe an end-to-end communication use case for an Industry 4.0 application scenario and to identify dependabilities in case of security challenges. Furthermore, we evaluate secure messaging protocols and the integration of Trusted Platform Module (TPM) as a root of trust for dataexchange. We define a set of representative measurable indicator points based on existing standards and use them for automated dependability detection within the whole system.
Towards flexible and secure end-to-end communication in industry 4.0
The digital transformation of industrial production is driven by the advance of cyber-physical production systems (CPPS) within which raw materials, machines and operations are interconnected to form a sophisticated network. Making such systems self-adaptable is a priority concern for the future implementation of Industry 4.0 application scenarios. In this position paper, we design a meta-model and use it as a tool to describe an end-to-end communication use case from an ongoing research project. Based on this use case we develop a business process performance and security trade-off model, which shows that maximazing both parameters at the same time is not possible, thus an efficient balance between them has to be achieved. Motivated by the result, we propose self adaptation as a solution towards a flexible and secure end-to-end communication in Industry 4.0. To identify and document the self-adaptation points in a structured methodological and lightweight way we use the bespoken meta-model.