Abstract
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OT objects in form of semantic relationships is often outdated or simply not available.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 of OT is missing. In order to counteract this fundamental deficiency,
we aim to automatically discover semantic relationships between OT objects, to build up an ontological knowledge base as
prerequisite for achieving OT situation awareness. Thereby, the contribution of this paper is threefold. First, a systematic
exploration of the induced challenges is provided, derived from an in-depth analysis of real-world OT message logs in the
area of RTM. Based on that, we sketch out a research roadmap, thereby guiding the identification of existing concepts and
technologies appearing to be useful for realizing a framework for semantic relationship awareness, being the crucial pre-
step for achieving OT situation awareness. Finally, a first proof-of-concept prototype is put forward, complemented by an
evaluation of its applicability and a detailed comparison to related approaches.
Keywords Critical infrastructure · Road traffic monitoring (RTM) · Operational tec
(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OT objects in form of semantic relationships is often outdated or simply not available.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 of OT is missing. In order to counteract this fundamental deficiency,
we aim to automatically discover semantic relationships between OT objects, to build up an ontological knowledge base as
prerequisite for achieving OT situation awareness. Thereby, the contribution of this paper is threefold. First, a systematic
exploration of the induced challenges is provided, derived from an in-depth analysis of real-world OT message logs in the
area of RTM. Based on that, we sketch out a research roadmap, thereby guiding the identification of existing concepts and
technologies appearing to be useful for realizing a framework for semantic relationship awareness, being the crucial pre-
step for achieving OT situation awareness. Finally, a first proof-of-concept prototype is put forward, complemented by an
evaluation of its applicability and a detailed comparison to related approaches.
Keywords Critical infrastructure · Road traffic monitoring (RTM) · Operational tec
| Original language | English |
|---|---|
| Article number | 769 |
| Number of pages | 17 |
| Journal | SN Computer Science |
| Volume | 5 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 08 Aug 2024 |
Fields of science
- 102015 Information systems
- 102027 Web engineering
- 102 Computer Sciences
- 102022 Software development
- 102001 Artificial intelligence
- 502007 E-commerce
- 505002 Data protection
- 102010 Database systems
- 102035 Data science
- 102033 Data mining
- 506002 E-government
- 102019 Machine learning
- 102006 Computer supported cooperative work (CSCW)
- 102028 Knowledge engineering
- 102016 IT security
- 202007 Computer integrated manufacturing (CIM)
- 102025 Distributed systems
- 509018 Knowledge management
- 102014 Information design