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| Over the last decades a number of guidelines have been proposed for best practices, frameworks, and cyber risk assessment in present computational environments. In order to improve cyber security vulnerability, in this work it is proposed and characterized a feasible methodology for problem solving that allows for the evaluation of cyber security in terms of an estimation of its entropic state, i.e., a predictive evaluation of its risk and vulnerabilities, or in other words, the cyber security level of such ecosystem. The analysis and development of such a model is based on a line of logical formalisms for Knowledge Representation and Reasoning, consistent with an Artificial Neural Networks approach to computing, a model that considers the cause behind the action. | 43.05 KB | Adobe PDF |
Advisor(s)
Abstract(s)
Over the last decades a number of guidelines have been proposed for best practices, frameworks, and cyber risk assessment in present computational environments. In order to improve cyber security vulnerability, in this work it is proposed and characterized a feasible methodology for problem solving that allows for the evaluation of cyber security in terms of an estimation of its entropic state, i.e., a predictive evaluation of its risk and vulnerabilities, or in other words, the cyber security level of such ecosystem. The analysis and development of such a model is based on a line of logical formalisms for Knowledge Representation and Reasoning, consistent with an Artificial Neural Networks approach to computing, a model that considers the cause behind the action.
Description
Conference name - 8th World Conference on Information Systems and Technologies, WorldCIST 2020; Conference date - 7 April 2020 - 10 April 2020; Conference code - 240259
EISBN - 9783030456979
EISBN - 9783030456979
Keywords
Entropy Cyber security Logic Programming Knowledge Representation and Reasoning Artificial Neural Networks
Pedagogical Context
Citation
Fernandes, F. et al. (2020). A Thermodynamic Assessment of the Cyber Security Risk in Healthcare Facilities. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1161. Springer, Cham. https://doi.org/10.1007/978-3-030-45697-9_44.
Publisher
Springer Nature
CC License
Without CC licence
