Abstract
The use of Open Radio Access Networks (Open RAN) in vehicular networks can lead to better connectivity, reliability, and performance. However, communication in this setting is often done over an unsecured wireless network, which creates a challenge in verifying the validity of received transactions by Internet of Vehicles (IoV) due to the untrusted network. It also creates a potential for attackers to tamper with the data content and conduct different IoV-related attacks. To address these issues, a new framework named 'STIoV' has been proposed for secure and trustworthy communication in IoV. The framework includes a mutual authentication scheme to register and exchange session keys among the IoV participants, and a credit-based trust management system to assign reputation scores for the vehicular devices. The latter scheme discards transactions with low credit scores. To overcome the complexity and variability of the IoV network, digital twin technology is used to map Road Side Units (RSU) servers into virtual space, which facilitates constructing the vehicular relation model. An Intrusion Detection System (IDS) based on deep learning techniques is also introduced to detect anomalies in the traffic flow. The legitimate data is further used by the blockchain scheme for transaction verification, block creation and addition. Finally, the proposed framework has been evaluated based on two network intrusion datasets, and the results show the accuracy and efficacy of STIoV in comparison to several recent state-of-the-art solutions.
Original language | English |
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Pages (from-to) | 9234-9246 |
Number of pages | 13 |
Journal | IEEE Transactions on Vehicular Technology |
Volume | 73 |
Issue number | 7 |
Early online date | 18 Dec 2023 |
DOIs | |
Publication status | Published - Jul 2024 |
Keywords
- Blockchain
- Blockchains
- Cloud computing
- Deep Learning
- Digital Twin
- Digital twins
- Internet of Vehicles (IoV)
- Intrusion Detection System (IDS)
- Radio access networks
- Security
- Servers
- Trust management
- Trustworthiness