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The ubiquitous presence of surveillance systems generates massive amounts of video data. Storage and analysis of this data in real-time is a substantial challenge. There is huge potential in representing data in machine-readable and machine-interpretable format due to the presence of hidden semantics in images and videos. However, such representation requires ontology, which calls for expert domain knowledge. In this paper, a novel NLP-guided approach to generate an ontology for multimedia representation and information retrieval is proposed. A semi-automatic NLP-guided framework, which extracts all possible relations among objects is presented. This framework leverages the textual data of the domain to generate possible descriptions and actions within the domain. Relations among objects get embedded as object properties, whereas the category of an object as a class. Features and attributes of objects encode the data properties of the ontology. The proposed ontology is compared with existing multimedia ontologies and evaluated with regard to its capability to represent relations occurring in benchmark datasets, demonstrating the completeness and thorough coverage of the domain concepts. Spatial reasoning rules are established using Semantic Web Rule Language (SWRL) rules, and information retrieval is demonstrated using Description Logic (DL) and SPARQL queries. The proposed NLP-guided ontology generation approach is general enough to help in the development of ontologies for other domains as well, by providing video and textual data of the domain of interest, with limited human involvement. • Object properties extraction with textbase and NLP-guided approach. • Frequency-based semantic refinement to enhance domain-specific relations. • A novel data-driven video surveillance ontology "VizITS" for the ITS domain. • Semantic information retrieval as events, metadata, and question-answering. [ABSTRACT FROM AUTHOR]

Modern industrial systems are enriched by cyber–physical devices and interconnections with business processes that enable flexible production, remote monitoring, control and maintenance. These systems are typically subject to multiple authorities which must cooperate with each other, as in the case of segmented industrial environments and supply chains. In similar contexts, voluntary or unintentional damages may be caused by cyber attacks or by misbehaving authorized parties. We propose an original architecture that regulates accesses to industrial systems' resources through authorization delegation procedures. It guarantees several benefits that include the possibility of auditing authorizations released by delegated third parties, of detecting misconducts and possible attacks, and of assuring attribution of misconducts. The proposed solution is compatible with constraints characterizing industrial environments and with security and performance requirements of industrial architectures. The performance and latencies of the auditing mechanisms are evaluated through a prototype. [ABSTRACT FROM AUTHOR]