Operations security evaluation of IaaS-cloud backend for industry 4.0
2018-03, Schluga, Oliver, Bauer, Elisabeth, Bicaku, Ani, Maksuti, Silia, Tauber, Markus, Wöhler, Alexander
The fast growing number of cloud based Infrastructure-as-a-Service instances raises the question, how the operations security depending on the underlying cloud computing infrastructure can be sustained and guaranteed. Security standards provide guidelines for information security controls applicable to the provision and use of the cloud services. The objectives of operations security are to support planning and sustaining of day-to-day processes that are critical with respect to security of information environments. In this work we provide a detailed analysis of ISO 27017 standard regarding security controls and investigate how well popular cloud platforms can cater for them. The resulting gap of support for individual security controls is furthermore compared with outcomes of recent cloud security research projects. Hence the contribution is twofold, first we identify a set of topics that still require research and development and secondly, as a practical output, we provide a comparison of popular industrial and open-source platforms focusing on private cloud environments, which are important for Industry 4.0 use cases.
Self-Adaptation Applied to MQTT via a Generic Autonomic Management Framework
2019-02, Maksuti, Silia, Schluga, Oliver, Settanni, Giuseppe, Tauber, Markus, Delsing, Jerker
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.
Towards a Security Baseline for IaaS-Cloud Back-Ends in Industry 4.0
2017-12, Bauer, Elisabeth, Schluga, Oliver, Maksuti, Silia, Bicaku, Ani, Hofbauer, David, Ivkić, Igor, Wöhrer, Alexander, Tauber, Markus
The popularity of cloud based Infrastructure-as-a- Service (IaaS) solutions is becoming increasingly popular. However, since IaaS providers and customers interact in a flexible and scalable environment, security remains a serious concern. To handle such security issues, defining a set of security parameters in the service level agreements (SLA) between both, IaaS provider and customer, is of utmost importance. In this paper, the European Network and Information Security Agency (ENISA) guidelines are evaluated to extract a set of security parameters for IaaS. Furthermore, the level of applicability and implementation of this set is used to assess popular industrial and open-source IaaS cloud platforms, respectively VMware and OpenStack. Both platforms provide private clouds, used as backend infrastructures in Industry 4.0 application scenarios. The results serve as initial work to identify a security baseline and research needs for creating secure cloud environments for Industry 4.0.