Abstract
The vehicular ad hoc network (VANET) is a method through which Intelligent Transportation Systems (ITS) have become important for the benefit of daily life. Real-time detection of all forms of attacks, including hybrid DoS attacks in IEEE 802.11p, has become an urgent issue for VANET. This is due to sporadic real-time exchange of safety and road emergency message delivery in VANET. Sporadic communication in VANET has the tendency to generate an enormous amount of messages. This leads to overutilization of the road side unit (RSU) or the central processing unit (CPU) for computation. Therefore, efficient storage and intelligent VANET infrastructure architecture (VIA), which includes trustworthiness, are required. Vehicular Cloud and Fog Computing (VFC) play an important role in efficient storage, computation, and communication needs for VANET. This research utilizes VFC integration with hybrid optimization algorithms (OAs), which also possess swarm intelligence, including Cuckoo/CSA Artificial Bee Colony (ABC) and Firefly/Genetic Algorithm (GA), to provide real-time detection of DoS attacks in IEEE 802.11p, using VFC for a secure intelligent vehicular network. Vehicles move ar a certain speed and the data is transmitted at 30 Mbps. Firefly Feed forward back propagation neural network (FFBPNN) is used as a classifier to distinguish between the attacked vehicles and the genuine vehicles. The proposed scheme is compared with Cuckoo/CSA ABC and Firefly GA by considering jitter, throughput, and prediction accuracy.
Highlights
In order to provide trust in the network, it is anticipated that hybrid DoS attacks (HDSA), including DoS Jamming Signal Attack (DoS JSA) and other attacks that may be hard to detect in the proposed scheme models, such as HDSA model (HDAM), proposed scheme system architecture model (PSAM), and PESATRM, have one solution that can be devised to evaluate the probability information received through a consensus mechanism [46]
We utilized single hop vehicle (SNHV) data transfer probability based upon the proposed scheme models (HDAM, and PSAM integrated with PESATRM) concerning the vehicle communication processes, which include V2V, V2RSU, and RSU2V communication
The vehicular ad hoc network (VANET) avoids heavy traffic conditions and driving problems that may be encountered on the roads, including highways
Summary
These OAs can be integrated with authentication and KDE mechanisms This integration with the real-time detection of HDSA can provide secure methods in the MAC layer, which in turn can be used to mitigate all forms of attacks, including HDSA, such as DoS JSA, PD, and RCRCO, which utilizes IEEE 802.11p beacon transmissions in VANET. This represents an urgent practical problem that we are motivated to investigate in this research
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