Timing Model for Predictive Simulation of Safety-Critical
Systems

D 2022

Timing Model for Predictive Simulation of Safety-Critical Systems

CIOROAICA, Emilia, José Miguel BLANCO SÁNCHEZ and Bruno ROSSI

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

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

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

Abstract

V originále

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 project

Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur

Citovat

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.

@inproceedings{1857658,
   author = {Cioroaica, Emilia and Blanco Sánchez, José Miguel and Rossi, Bruno},
   address = {Not specified},
   booktitle = {17th International Conference on Software Technologies (ICSOFT 2022)},
   doi = {http://dx.doi.org/10.5220/0011317000003266},
   keywords = {Runtime Prediction; Predictive Simulation; Malicious Behavior; Virtual Evaluation; Trust; Automotive},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Not specified},
   isbn = {978-989-758-588-3},
   pages = {331-339},
   publisher = {SciTePress},
   title = {Timing Model for Predictive Simulation of Safety-Critical Systems},
   year = {2022}
}

TY  - JOUR
ID  - 1857658
AU  - Cioroaica, Emilia - Blanco Sánchez, José Miguel - Rossi, Bruno
PY  - 2022
TI  - Timing Model for Predictive Simulation of Safety-Critical Systems
PB  - SciTePress
CY  - Not specified
SN  - 9789897585883
KW  - Runtime Prediction
KW  - Predictive Simulation
KW  - Malicious Behavior
KW  - Virtual Evaluation
KW  - Trust
KW  - Automotive
N2  - 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.
ER  -

CIOROAICA, Emilia, José Miguel BLANCO SÁNCHEZ and Bruno ROSSI. Timing Model for Predictive Simulation of Safety-Critical Systems. Online. In \textit{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.

Detailed Information on Publication Record