(Do not) trust in ecosystems

CIOROAICA, Emilia, Thomas KUHN and Barbora BÜHNOVÁ. (Do not) trust in ecosystems. Online. In Proceedings of the 41st International Conference on Software Engineering: New Ideas and Emerging Results. USA: IEEE Press, 2019, p. 9-12. ISBN 978-1-72811-758-4. Available from: https://dx.doi.org/10.1109/ICSE-NIER.2019.00011.

Basic information

• Original name: (Do not) trust in ecosystems
• Authors: CIOROAICA, Emilia (642 Romania), Thomas KUHN (276 Germany) and Barbora BÜHNOVÁ (203 Czech Republic, guarantor, belonging to the institution).
• Edition: USA, Proceedings of the 41st International Conference on Software Engineering: New Ideas and Emerging Results, p. 9-12, 4 pp. 2019.
• Publisher: IEEE Press

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10200 1.2 Computer and information sciences
• Country of publisher: United States of America
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: electronic version available online
• WWW: URL
• RIV identification code: RIV/00216224:14330/19:00110162
• Organization unit: Faculty of Informatics
• ISBN: 978-1-72811-758-4
• Doi: http://dx.doi.org/10.1109/ICSE-NIER.2019.00011
• UT WoS: 000557879900003
• Keywords in English: Automotive; building trust; malicious behavior; smart ecosystems; virtual evaluation
• Tags: International impact, Reviewed

Abstract

In the context of Smart Ecosystems, systems engage in dynamic cooperation with other systems to achieve their goals. Expedient operation is only possible when all systems cooperate as expected. This requires a level of trust between the components of the ecosystem. New systems that join the ecosystem therefore first need to build up a level of trust. Humans derive trust from behavioral reputation in key situations. In Smart Ecosystems (SES), the reputation of a system or system component can also be based on observation of its behavior. In this paper, we introduce a method and a test platform that support virtual evaluation of decisions at runtime, thereby supporting trust building within SES. The key idea behind the platform is that it employs and evaluates Digital Twins, which are executable models of system components, to learn about component behavior in observed situations. The trust in the Digital Twin then builds up over time based on the behavioral compliance of the real system component with its Digital Twin. In this paper, we use the context of automotive ecosystems and examine the concepts for building up reputation on control algorithms of smart agents dynamically downloaded at runtime to individual autonomous vehicles within the ecosystem.

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