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

D 2024

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

BANGUI, Hind, Barbora BÜHNOVÁ and Daša KUŠNIRÁKOVÁ

Basic information

Original name

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

Authors

BANGUI, Hind (504 Morocco, belonging to the institution), Barbora BÜHNOVÁ (203 Czech Republic, guarantor, belonging to the institution) and Daša KUŠNIRÁKOVÁ (703 Slovakia, belonging to the institution)

Edition

Lisbon, PORTUGAL, The 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2024), p. 53-56, 4 pp. 2024

Publisher

ACM/IEEE

Other information

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

References:

URL

Organization unit

Faculty of Informatics

ISBN

979-8-4007-0557-1

DOI

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

UT WoS

001293142100008

Keywords in English

Trust Management; IoT; IoV; Ethics; Behavior

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.

Links

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

Citovat

BANGUI, Hind, Barbora BÜHNOVÁ and Daša KUŠNIRÁKOVÁ. Exploring Trust Black-Swan Blindness in Social Internet of Vehicles (SIoV). Online. In ACM/IEEE. The 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2024). Lisbon, PORTUGAL: ACM/IEEE, 2024, p. 53-56. ISBN 979-8-4007-0557-1. Available from: https://dx.doi.org/10.1145/3643655.3643877.

@inproceedings{2361254,
   author = {Bangui, Hind and Bühnová, Barbora and Kušniráková, Daša},
   address = {Lisbon, PORTUGAL},
   booktitle = {The 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2024)},
   doi = {http://dx.doi.org/10.1145/3643655.3643877},
   editor = {ACM/IEEE},
   keywords = {Trust Management; IoT; IoV; Ethics; Behavior},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Lisbon, PORTUGAL},
   isbn = {979-8-4007-0557-1},
   pages = {53-56},
   publisher = {ACM/IEEE},
   title = {Exploring Trust Black-Swan Blindness in Social Internet of Vehicles (SIoV)},
   url = {https://doi.org/10.1145/3643655.3643877},
   year = {2024}
}

TY  - CONF
ID  - 2361254
AU  - Bangui, Hind - Bühnová, Barbora - Kušniráková, Daša
PY  - 2024
TI  - Exploring Trust Black-Swan Blindness in Social Internet of Vehicles (SIoV)
PB  - ACM/IEEE
CY  - Lisbon, PORTUGAL
SN  - 9798400705571
KW  - Trust Management
KW  - IoT
KW  - IoV
KW  - Ethics
KW  - Behavior
UR  - https://doi.org/10.1145/3643655.3643877
N2  - 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.
ER  -

BANGUI, Hind, Barbora BÜHNOVÁ and Daša KUŠNIRÁKOVÁ. Exploring Trust Black-Swan Blindness in Social Internet of Vehicles (SIoV). Online. In ACM/IEEE. \textit{The 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2024)}. Lisbon, PORTUGAL: ACM/IEEE, 2024, p.~53-56. ISBN~979-8-4007-0557-1. Available from: https://dx.doi.org/10.1145/3643655.3643877.

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