Exploring Trust Black-Swan Blindness in Social Internet of Vehicles (SIoV)
| Authors | |
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| Year of publication | 2024 |
| Type | Article in Proceedings |
| Conference | The 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2024) |
| MU Faculty or unit | |
| Citation | |
| web | https://doi.org/10.1145/3643655.3643877 |
| Doi | http://dx.doi.org/10.1145/3643655.3643877 |
| Description | 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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