CRT-BIoV: a cognitive radio technique for blockchain-enabled internet of vehicles

G Rathee, F Ahmad, F Kurugollu… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
IEEE Transactions on Intelligent Transportation Systems, 2020ieeexplore.ieee.org
Cognitive Radio Network (CRN) is considered as a viable solution on Internet of Vehicle
(IoV) where objects equipped with cognition make decisions intelligently through the
understanding of both social and physical worlds. However, the spectrum availability and
data sharing/transferring among vehicles are critical improving services and driving safety
metrics where the presence of Malicious Devices (MD) further degrade the network
performance. Recently, a blockchain technique in CRN-based IoV has been introduced to …
Cognitive Radio Network (CRN) is considered as a viable solution on Internet of Vehicle (IoV) where objects equipped with cognition make decisions intelligently through the understanding of both social and physical worlds. However, the spectrum availability and data sharing/transferring among vehicles are critical improving services and driving safety metrics where the presence of Malicious Devices (MD) further degrade the network performance. Recently, a blockchain technique in CRN-based IoV has been introduced to prevent data alteration from these MD and allowing the vehicles to track both legal and illegal activities in the network. In this paper, we provide the security to IoV during spectrum sensing and information transmission using CRN by sensing the channels through a decision-making technique known as Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), a technique that evokes the trust of its Cognitive Users (CU) by analyzing certain predefined attributes. Further, blockchain is maintained in the network to trace every activity of stored information. The proposed mechanism is validated rigorously against several security metrics using various spectrum sensing and security parameters against a baseline solution in IoV. Extensive simulations suggest that our proposed mechanism is approximately 70% more efficient in terms of malicious nodes identification and DoS threat against the baseline mechanism.
ieeexplore.ieee.org
以上显示的是最相近的搜索结果。 查看全部搜索结果