Exploring Trust Black-Swan Blindness in Social Internet of Vehicles (SIoV)

BANGUI, Hind, Barbora BÜHNOVÁ and Daša KUŠNIRÁKOVÁ. Exploring Trust Black-Swan Blindness in Social Internet of Vehicles (SIoV). In The 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2024). ACM/IEEE, 2024. Available from: https://dx.doi.org/10.1145/3643655.3643877.

Basic information

Original name

Exploring Trust Black-Swan Blindness in Social Internet of Vehicles (SIoV)

Authors

BANGUI, Hind, Barbora BÜHNOVÁ and Daša KUŠNIRÁKOVÁ

Edition

The 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2024), 2024

Publisher

ACM/IEEE

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Organization unit

Faculty of Informatics

DOI

http://dx.doi.org/10.1145/3643655.3643877

Tags

International impact, Reviewed

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Abstract

V originále

Bringing social networking notions into the Internet of Vehicles (IoV) paradigm has defined Social IoV ecosystems as an extension of the Social Internet of Things (SIoT). SIoV ecosystems have increased the smart utilization of transport networks by enabling vehicles to communicate autonomously and share information about their surrounding environment. However, the ability of vehicles to establish social relationships autonomously with different IoV entities has inherited the primary challenge in SIoT, which is to establish trusted relationships. This is further emphasized by the dynamic nature of vehicular ecosystems that allow various kinds of misbehaviour to be unnoticed, leading to scarce trust evidence and increased risk of blind spots in trust management. In this work, we introduce our trust-management vision for SIoV by gaining from the Black Swan theory to turn unnoticeable malicious behaviors into noticeable ones, and create a true sense of trust in SIoV.

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Links

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
MUNI/A/1586/2023, interní kód MU	Name: Aplikovaný výzkum na FI: Forenzní aspekty kritických infrastruktur, aplikovaná kryptografie, kyberbezpečnostní cvičení, algoritmy plánování v logistice a pro zpracování dat z fyzikálních sensorů Investor: Masaryk University, Applied research at FI: Forensic aspects of critical infrastructures, applied cryptography, cybersecurity trainings, scheduling algorithms logistics and algorithms for physical sensors
MUNI/G/1142/2022, interní kód MU	Name: Forensic Support for Building Trust in Smart Software Ecosystems Investor: Masaryk University, Forensic Support for Building Trust in Smart Software Ecosystems, INTERDISCIPLINARY - Interdisciplinary research projects