TY - GEN
T1 - Towards Automating Semantic Relationship Awareness in Operational Technology Monitoring
AU - Schwinger, Wieland
AU - Kapsamer, Elisabeth
AU - Retschitzegger, Werner
AU - Pröll, Birgit
AU - Graf, David
AU - Baumgartner, Norbert
AU - Schönböck, Johannes
AU - Zaunmair, Herbert
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.
PY - 2023
Y1 - 2023
N2 - Critical infrastructures in areas like road traffic management naturally rely on the broad use of “Operational Technology (OT)” to ensure efficient and safe road traffic monitoring (RTM) through “OT objects” like sensors and actuators whereby monitoring OT itself (“OTM”) is evenly crucial. OTM is highly challenging, not least due to massive heterogeneity of OT, immense complexity and size and omnipresence of evolution. As a consequence, knowledge about interdependencies between OT objects in form of semantic relationships is often outdated or simply not available. Thus, in case of incidents, detection of cause and effect in the sense of a situational picture is missing. In order to counteract this fundamental deficiency, we aim to automatically recognize semantic relationships between OT objects to build up an ontological knowledge base as prerequisite for achieving OT situation awareness. The contribution of this paper is to sketch out state-of-research w.r.t. real-world challenges we are facing and based on that to put forward appropriate research questions, leading to the identification and in-depth discussion of potential concepts and technologies appearing to be useful for our work. Overall, this contribution forms the conceptual framework for a proof-of-concept prototype already realized on basis of real-world OT in the area of road traffic management.
AB - Critical infrastructures in areas like road traffic management naturally rely on the broad use of “Operational Technology (OT)” to ensure efficient and safe road traffic monitoring (RTM) through “OT objects” like sensors and actuators whereby monitoring OT itself (“OTM”) is evenly crucial. OTM is highly challenging, not least due to massive heterogeneity of OT, immense complexity and size and omnipresence of evolution. As a consequence, knowledge about interdependencies between OT objects in form of semantic relationships is often outdated or simply not available. Thus, in case of incidents, detection of cause and effect in the sense of a situational picture is missing. In order to counteract this fundamental deficiency, we aim to automatically recognize semantic relationships between OT objects to build up an ontological knowledge base as prerequisite for achieving OT situation awareness. The contribution of this paper is to sketch out state-of-research w.r.t. real-world challenges we are facing and based on that to put forward appropriate research questions, leading to the identification and in-depth discussion of potential concepts and technologies appearing to be useful for our work. Overall, this contribution forms the conceptual framework for a proof-of-concept prototype already realized on basis of real-world OT in the area of road traffic management.
KW - Critical Infrastructure
KW - Ontologies
KW - Operational Technology Monitoring (OTM)
KW - Road traffic management
KW - Semantic Relationships
UR - http://www.scopus.com/inward/record.url?scp=85177826672&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-8296-7_39
DO - 10.1007/978-981-99-8296-7_39
M3 - Conference contribution
SN - 9789819982950
T3 - Communications in Computer and Information Science
SP - 545
EP - 555
BT - Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 10th International Conference, FDSE 2023, Proceedings
A2 - Dang, Tran Khanh
A2 - Küng, Josef
A2 - Chung, Tai M.
ER -