CIOROAICA, Emilia, José Miguel BLANCO SÁNCHEZ and Bruno ROSSI. Timing Model for Predictive Simulation of Safety-Critical Systems. Online. In 17th International Conference on Software Technologies (ICSOFT 2022). Not specified: SciTePress, 2022, p. 331-339. ISBN 978-989-758-588-3. Available from: https://dx.doi.org/10.5220/0011317000003266.
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Basic information
Original name Timing Model for Predictive Simulation of Safety-Critical Systems
Authors CIOROAICA, Emilia (642 Romania), José Miguel BLANCO SÁNCHEZ (724 Spain, guarantor, belonging to the institution) and Bruno ROSSI (380 Italy, belonging to the institution).
Edition Not specified, 17th International Conference on Software Technologies (ICSOFT 2022), p. 331-339, 9 pp. 2022.
Publisher SciTePress
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
RIV identification code RIV/00216224:14330/22:00125921
Organization unit Faculty of Informatics
ISBN 978-989-758-588-3
Doi http://dx.doi.org/10.5220/0011317000003266
UT WoS 000852747000033
Keywords in English Runtime Prediction; Predictive Simulation; Malicious Behavior; Virtual Evaluation; Trust; Automotive
Tags core_B, firank_B
Tags International impact, Reviewed
Changed by Changed by: Bruno Rossi, PhD, učo 232464. Changed: 13/3/2023 09:33.
Abstract
Emerging evidence shows that safety-critical systems are evolving towards operating in uncertain context while integrating intelligent software that evolves over time as well. Such behavior is considered to be unknown at every moment in time because when faced with a similar situation, these systems are expected to display an improved behavior based on artificial learning. Yet, a correct learning and knowledge-building process for the non-deterministic nature of an intelligent evolution is still not guaranteed and consequently safety of these systems cannot be assured. In this context, the approach of predictive simulation enables runtime predictive evaluation of a system behavior and provision of quantified evidence of trust that enables a system to react safety in case malicious deviations, in a timely manner. For enabling the evaluation of timing behavior in a predictive simulation setting, in this paper we introduce a general timing model that enables the virtual execution of a system's timing behavior. The predictive evaluation of the timing behavior can be used to evaluate a system's synchronization capabilities and in case of delays, trigger a safe fail-over behavior. We iterate our concept over an use case from the automotive domain by considering two safety critical situations.
Links
CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU
(CEP code: EF16_019/0000822)
Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Acronym: C4e)
Investor: Ministry of Education, Youth and Sports of the CR, CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence, Priority axis 1: Strengthening capacities for high-quality research
EF16_019/0000822, research and development projectName: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur
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