TY - CHAP A1 - Neubauer, Katrin A1 - Fischer, Sebastian A1 - Hackenberg, Rudolf ED - Trinitis, Carsten ED - Pionteck, Thilo T1 - Work in Progress: Security Analysis for Safety-critical Systems BT - Smart Grid and IoT T2 - ARCS Workshop 2019; 32nd International Conference on Architecture of Computing Systems, May 2019, Copenhagen, Denmark, Workshop FORMUS³IC N2 - Internet of Thing (IoT) and Smart Grid (SG) are separate technologies. The digital transformation of the energy industry and the increasing digitalization in the private sector connect these technologies. Currently in Germany, the SG is under construction. In order to use future innovative services, SG and IoT must be combined. For this, we connect the SG Infrastructure with the IoT. A potential insecure device and network (IoT) should be able to transfer data to and from a critical infrastructure (SG). Open research question in this context are the security requirements architecture SG and IoT and the mechanism for authentication and authorisation in future application (SG and IoT). Due to the increasing networking of the systems (SG and IoT) new threats and attack vectors arise. The attacks to the architecture influence the target of authenticity, security and privacy. For the security analysis we focus on two communication points: the communication between the smart meter gateway, and the IoT device. In our example, a connected charging station with cloud services is connected with a SG infrastructure. To create a really smart service, the charging station needs a connection to the SG to get the current amount of renewable energy in the grid. With this two connections, new threats emerge. A security analysis over all the connections, including the vulnerability and the ability of an attacker, is developed in this paper. The analysis shows us challenges of the communication between IoT and SG. For this, we defined technical and organizational requirements for authentication and authorization. Current authentication and authorization mechanisms are no longer sufficient for the defined requirements. We present the Role-based trust model for Safety-critical Systems for these defined requirements. The new trust model is integrated into a role-based access control model. It defines data classes, which separate the sensitive and non-sensitive information. KW - smart grid KW - Internet of Things (IoT) KW - security analysis; KW - safety-critical infrastructure KW - trust model Y1 - 2019 SN - 978-3-8007-4957-7 SP - 101 EP - 106 PB - VDE Verlag GmbH CY - Berlin ER - TY - CHAP A1 - Vogl, Peter A1 - Weber, Sergei A1 - Graf, Julian A1 - Neubauer, Katrin A1 - Hackenberg, Rudolf T1 - Design and Implementation of an Intelligent and Model-based Intrusion Detection System for Iot Networks T2 - Cloud Computing 2022: The Thirteenth International Conference on Cloud Computing, GRIDs, and Virtualization, Special Track FAST-CSP, Barcelona, Spain, 24.-28.04.2022 N2 - The ongoing digitization and digitalization entails the increasing risk of privacy breaches through cyber attacks. Internet of Things (IoT) environments often contain devices monitoring sensitive data such as vital signs, movement or surveil-lance data. Unfortunately, many of these devices provide limited security features. The purpose of this paper is to investigate how artificial intelligence and static analysis can be implemented in practice-oriented intelligent Intrusion Detection Systems to monitor IoT networks. In addition, the question of how static and dynamic methods can be developed and combined to improve net-work attack detection is discussed. The implementation concept is based on a layer-based architecture with a modular deployment of classical security analysis and modern artificial intelligent methods. To extract important features from the IoT network data a time-based approach has been developed. Combined with network metadata these features enhance the performance of the artificial intelligence driven anomaly detection and attack classification. The paper demonstrates that artificial intelligence and static analysis methods can be combined in an intelligent Intrusion Detection System to improve the security of IoT environments. KW - Intrusion Detection KW - Artificial Intelligence KW - Machine Learning KW - Network Security KW - Internet of Things Y1 - 2022 UR - https://www.thinkmind.org/index.php?view=article&articleid=cloud_computing_2022_1_20_28003 SN - 978-1-61208-948-5 SP - 7 EP - 12 PB - IARIA CY - [Wilmington, DE, USA] ER - TY - CHAP A1 - Hinterberger, Lukas A1 - Weber, Bernhard A1 - Fischer, Sebastian A1 - Neubauer, Katrin A1 - Hackenberg, Rudolf T1 - IoT Device IdentificAtion and RecoGnition (IoTAG) T2 - CLOUD COMPUTING 2020, The Eleventh International Conference on Cloud Computing, GRIDs and Virtualization N2 - To ensure the secure operation of IoT devices in the future, they must be continuously monitored. This starts with an inventory of the devices, checking for a current software version and extends to the encryption algorithms and active services used. Based on this information, a security analysis and rating of the whole network is possible. To solve this challenge in the growing network environments, we present a proposal for a standard. With the IoT Device IdentificAtion and RecoGnition (IoTAG), each IoT device reports its current status to a central location as required and provides information on security. This information includes a unique ID, the exact device name, the current software version, active services, cryptographic methods used, etc. The information is signed to make misuse more difficult and to ensure that the device can always be uniquely identified. In this paper, we introduce IoTAG in detail and describe the necessary requirements. KW - Internet of Things KW - device identification KW - IoTAG KW - security rating Y1 - 2020 UR - https://thinkmind.org/articles/cloud_computing_2020_2_10_28002.pdf SN - 978-1-61208-778-8 SP - 17 EP - 23 PB - IARIA ER - TY - CHAP A1 - Neubauer, Katrin A1 - Fischer, Sebastian A1 - Hackenberg, Rudolf T1 - Risk Analysis of the Cloud Infrastructure of Smart Grid and Internet of Things T2 - The Tenth International Conference on Cloud Computing, GRIDs, and Virtualization, (CLOUD COMPUTING 2019), 10th Mai 2019, Venice, Italy N2 - Cloud Computing (CC), Internet of Thing (IoT) and Smart Grid (SG) are separate technologies. The digital transformation of the energy industry and the increasing digitalization in the private sector connect these technologies. At the moment, CC is used as a service provider for IoT. Currently in Germany, the SG is under construction and a cloud connection to the infrastructure has not been implemented yet. To build the SG cloud, the new laws for privacy must be implemented and therefore it’s important to know which data can be stored and distributed over a cloud. In order to be able to use future innovative services, SG and IoT must be combined. For this, in the next step we connect the SG infrastructure with the IoT. A potential insecure device and network (IoT) should be able to transfer data to and from a critical infrastructure (SG). In detail, we focus on two different connections: the communication between the smart meter switching box and the IoT device and the data transferred between the IoT and SG cloud. In our example, a connected charging station with cloud services is connected with a SG infrastructure. To create a really smart service, the charging station needs a connection to the SG to get the current amount of renewable energy in the grid. Private data, such as name, address and payment details, should not be transferred to the IoT cloud. With these two connections, new threads emerge. In this case, availability, confidentiality and integrity must be ensured. A risk analysis over all the cloud connections, including the vulnerability and the ability of an attacker and the resulting risk are developed in this paper. KW - Smart Grid KW - Internet of Things KW - security analysis KW - cloud computing KW - safety-critical infrastructure Y1 - 2019 UR - https://www.thinkmind.org/articles/cloud_computing_2019_6_20_28013.pdf SN - 978-1-61208-703-0 SN - 2308-4294 SP - 82 EP - 87 PB - IARIA ER - TY - CHAP A1 - Fischer, Sebastian A1 - Neubauer, Katrin A1 - Hackenberg, Rudolf T1 - A Study about the Different Categories of IoT in Scientific Publications T2 - CLOUD COMPUTING 2020: the Eleventh International Conference on Cloud Computing, GRIDs and Virtualization, October 25-29, 2020, Nizza N2 - The Internet of Things (IoT) is widely used as a synonym for nearly every connected device. This makes it really difficult to find the right kind of scientific publication for the intended category of IoT. Conferences and other events for IoT are confusing about the target group (consumer, enterprise, industrial, etc.) and standardisation organisations suffer from the same problem. To demonstrate these problems, this paper shows the results of an analyses over IoT publications in different research libraries. The number of results for IoT, consumer, enterprise and industrial search queries were evaluated and a manual study about 100 publications was done. According to the research library or search engine, different results about the distribution of consumer-, enterprise- and industrial- IoT are visible. The comparison with the results of the manual evaluation shows that some search queries do not show all desired publications or that considerably more, unwanted results are returned. Most researchers do not use the keywords right and the exact category of IoT can only be accessed via the abstract. This shows major problems with the use of the term IoT and its minor limitations. KW - Internet of Things KW - IoT KW - publications KW - consumer KW - industrial KW - enterprise KW - categorization Y1 - 2020 UR - https://thinkmind.org/articles/cloud_computing_2020_2_20_28004.pdf SN - 978-1-61208-778-8 SP - 24 EP - 30 PB - IARIA ER - TY - JOUR A1 - Neubauer, Katrin A1 - Fischer, Sebastian A1 - Hackenberg, Rudolf T1 - Security risk analysis of the cloud infrastructure of Smart Grid and IoT - 4-Level-Trust-Model as a security solution JF - International Journal on Advances in Internet Technology N2 - The digital transformation has found its way into business and private life. It consists of digitization and digitaliza- tion. Digitization means the technical process and digitalization is the socio-technological process. Technologies of digitization are Cloud Computing (CC), Internet of Things (IoT) and Smart Grid (SG), which are separate technologies. The increasing digitalization in the private sector and of the energy industry connect these technologies. Actually, there is no connection between the CC infrastructure and the SG infrastructure at the moment, because in Germany the SG is currently under construction. If one looks at the CC and IoT, it must be stated there is an connection between the IoT infrastructure and the CC infrastructure as a service provider. To connect the technologies CC, IoT and SG and also build an SG cloud for innovative services, the new laws for privacy must be implemented. For privacy and security analyses it is important to know which data can be stored and distributed on a cloud. To illustrate this analysis, we connect the SG infrastructure with the IoT. An IoT device (car charging station) should be able to transfer data to and from the SG. SG is a critical infrastructure and the IoT device a potential insecure device and network. We show the communication between the smart meter switching box and the IoT device and the data transferred between their clouds. The charging station is connected to the SG to get the current amount of renewable energy in the grid. This is necessary to create a new smart service. But this service also generates private data (e.g., name, address, payment details). The private data should not be transferred to the IoT cloud. For the connection of SG and IoT, availability, confidentiality and integrity must be ensured. A risk analysis over all the cloud connections, including the vulnerability and the ability of an attacker, the resulting risk and the 4-Level- Trust-Model for security assessment are developed. Furthermore, we show the application of the 4-Level-Trust-Model in this paper. Y1 - 2020 UR - https://www.researchgate.net/publication/346580224_Security_Risk_Analysis_of_the_Cloud_Infrastructure_of_Smart_Grid_and_IoT_-_4-Level-Trust-Model_as_a_Security_Solution UR - https://www.iariajournals.org/internet_technology/inttech_v13_n12_2020_paged.pdf VL - 13 IS - 1&2 SP - 11 EP - 20 ER -