scholarly journals Ontology-Based System for Dynamic Risk Management in Administrative Domains

2019 ◽  
Vol 9 (21) ◽  
pp. 4547 ◽  
Author(s):  
Mario Vega-Barbas ◽  
Víctor A. Villagrá ◽  
Fernando Monje ◽  
Raúl Riesco ◽  
Xavier Larriva-Novo ◽  
...  

With the increasing complexity of cyberthreats, it is necessary to have tools to understand the changing context in real-time. This document will present architecture and a prototype designed to model the risk of administrative domains, exemplifying the case of a country in real-time, specifically, Spain. In order to carry out this task, a modeling of the assets and threats detected by various sources of information has been carried out. All this information is stored as knowledge making use of ontologies, which enables the application of reasoning engines in order to infer new knowledge that can be used later in the following reasoning. This modeling and reasoning have been enriched with a dynamic system for managing the trust of the different sources of information and capabilities for increased reliability with the inclusion of additional threat intelligence information.

2016 ◽  
Author(s):  
Andrew Hartigan ◽  
Darryl Thrasher ◽  
Robin Adlam

2021 ◽  
Vol 12 ◽  
Author(s):  
John A. Donaghy ◽  
Michelle D. Danyluk ◽  
Tom Ross ◽  
Bobby Krishna ◽  
Jeff Farber

Foodborne pathogens are a major contributor to foodborne illness worldwide. The adaptation of a more quantitative risk-based approach, with metrics such as Food safety Objectives (FSO) and Performance Objectives (PO) necessitates quantitative inputs from all stages of the food value chain. The potential exists for utilization of big data, generated through digital transformational technologies, as inputs to a dynamic risk management concept for food safety microbiology. The industrial revolution in Internet of Things (IoT) will leverage data inputs from precision agriculture, connected factories/logistics, precision healthcare, and precision food safety, to improve the dynamism of microbial risk management. Furthermore, interconnectivity of public health databases, social media, and e-commerce tools as well as technologies such as blockchain will enhance traceability for retrospective and real-time management of foodborne cases. Despite the enormous potential of data volume and velocity, some challenges remain, including data ownership, interoperability, and accessibility. This paper gives insight to the prospective use of big data for dynamic risk management from a microbiological safety perspective in the context of the International Commission on Microbiological Specifications for Foods (ICMSF) conceptual equation, and describes examples of how a dynamic risk management system (DRMS) could be used in real-time to identify hazards and control Shiga toxin-producing Escherichia coli risks related to leafy greens.


Author(s):  
Adriano A. Rampini ◽  
Amir Sufi ◽  
S. "Vish" Viswanathan

2014 ◽  
Vol 111 (2) ◽  
pp. 271-296 ◽  
Author(s):  
Adriano A. Rampini ◽  
Amir Sufi ◽  
S. Viswanathan

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