Secure Communication Protocols for Software-Defined Vehicles: A Machine Learning Approach
Keywords:
Autonomous vehicle, Software-defined vehicle, Machine Learning.Abstract
Software-defined networking, sometimes known as SDN for short, is an intriguing method of networking that combines centralized management with network programming. When software-defined networking (SDN) is utilized, the control plane and the data plane are separated, and the network management is transferred to a central place known as the controller. In addition to being able to be programmed, this controller acts as the brain of the network. Over the past few years, the research community has shown a rising tendency to reap the benefits of current discoveries in artificial intelligence (AI) to increase their capacity for learning and decision-making in software-defined networking (SDN). It has been established that they have this propensity to boost their capacity to learn and to make judgments. This paper comprehensively overviews recent initiatives undertaken to incorporate AI into SDN. According to our research findings, the most often discussed topics in artificial intelligence were machine learning, meta-heuristics, and fuzzy inference systems. This study aims to evaluate the potential advantages of introducing AI-based approaches into the SDN paradigm and the possible uses and applications for these methodologies.
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