Conceptual Framework for Adaptive Safety in Autonomous Ecosystems.

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00130846" target="_blank" >RIV/00216224:14330/23:00130846 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.5220/0012086600003538" target="_blank" >https://doi.org/10.5220/0012086600003538</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0012086600003538" target="_blank" >10.5220/0012086600003538</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Conceptual Framework for Adaptive Safety in Autonomous Ecosystems.

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Conceptual Framework for Adaptive Safety in Autonomous Ecosystems.

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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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

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 18th International Conference on Software Technologies - ICSOFT

ISBN

9789897586651

ISSN

2184-2833

e-ISSN

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Počet stran výsledku

11

Strana od-do

393-403

Název nakladatele

SciTePress

Místo vydání

Neuveden

Místo konání akce

Řím, Itálie

Datum konání akce

1. 1. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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