Timing Model for Predictive Simulation of Safety-Critical Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00125921" target="_blank" >RIV/00216224:14330/22:00125921 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5220/0011317000003266" target="_blank" >http://dx.doi.org/10.5220/0011317000003266</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0011317000003266" target="_blank" >10.5220/0011317000003266</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Timing Model for Predictive Simulation of Safety-Critical Systems

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Timing Model for Predictive Simulation of Safety-Critical Systems

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

17th International Conference on Software Technologies (ICSOFT 2022)

ISBN

9789897585883

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

331-339

Název nakladatele

SciTePress

Místo vydání

Not specified

Místo konání akce

Lisbon, Portugal

Datum konání akce

11. 7. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000852747000033