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2022-02-03
Maksuti, Silia, Pickem, Michael, Zsilak, Mario, Stummer, Anna, Tauber, Markus, Wieschhoff, Marcus, Pirker, Dominic, Schmittner, Christoph, Delsing, Jerker.  2021.  Establishing a Chain of Trust in a Sporadically Connected Cyber-Physical System. 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM). :890—895.
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.
2020-08-24
Maksuti, Silia, Schluga, Oliver, Settanni, Giuseppe, Tauber, Markus, Delsing, Jerker.  2019.  Self-Adaptation Applied to MQTT via a Generic Autonomic Management Framework. 2019 IEEE International Conference on Industrial Technology (ICIT). :1179–1185.
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.