Machine Learning-Based Jamming Detection for Safety Applications in Vehicular Networks: Individual Detection?

Table 1

Related works on jamming detection in vehicular networks.

Methods	Advantages	Disadvantages
RF jamming detection [10]	Simple and feasible to implement	Use case is specified for communication between two vehicles
Real-time detection [8] (TVT)	High detection probability, dedicated to broadcasting in VANET	Susceptible to environment change, weak for individual observations
Machine learning-based detection [12]	High performance, real (experimental) data	Use case is specified for communication between two vehicles
AI-based detection [9]	Applicable for broadcasting, can be coupled with other methods	Based on synthetic data
Our proposed approach	Can be independently implemented at individual vehicles, applicable for broadcasting	Relied on training data