D 2023

Conceptual Framework for Adaptive Safety in Autonomous Ecosystems.

HALÁSZ, Dávid and Barbora BÜHNOVÁ

Basic information

Original name

Conceptual Framework for Adaptive Safety in Autonomous Ecosystems.

Authors

HALÁSZ, Dávid (703 Slovakia, guarantor, belonging to the institution) and Barbora BÜHNOVÁ (203 Czech Republic, belonging to the institution)

Edition

Neuveden, Proceedings of the 18th International Conference on Software Technologies - ICSOFT, p. 393-403, 11 pp. 2023

Publisher

SciTePress

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Portugal

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

RIV identification code

RIV/00216224:14330/23:00130846

Organization unit

Faculty of Informatics

ISBN

978-989-758-665-1

ISSN

DOI

Keywords in English

Autonomous Collaborative Ecosystems; Adaptive Safety; Software Architecture; Trust; Security; Autonomous Vehicles; Smart Agents; Digital Twins

Tags

Tags

International impact, Reviewed
Změněno: 7/2/2024 19:26, doc. Ing. RNDr. Barbora Bühnová, Ph.D.

Abstract

V originále

The dynamic collaboration among hyper-connected Autonomous Systems promotes their evolution towards Autonomous Ecosystems. In order to maintain the safety of such structures, it is essential to ensure that there is a certain level of understanding of the present and future behavior of individual systems in these ecosystems. Adaptive Safety is a promising direction to control access to features between cooperating systems. However, it requires information about its collaborators within the environment. Digital Twins could be used to predict possible future behavior of a system. This paper introduces a conceptual framework for Adaptive Safety that is being triggered based on the trust score computed from the predictive simulation of Digital Twins, which we suggest to use in Autonomous Ecosystems to load and safely execute third-party Smart Agents. By quantifying trust towards the agent and combining it with a decision tree, we leverage this as a deciding factor to conceal or expose certain features among collaborating systems.

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
MUNI/A/1389/2022, interní kód MU
Name: Aplikovaný výzkum na FI: Bezpečnost počítačových systémů, softwarových architektur kritických infrastruktur s forenzními aspekty, zpracování dat pokročilých sensorů a algoritmy plánování v dopravě a logistice
Investor: Masaryk University