Artificial Intelligence Techniques in Vehicular Cloud Computing Security

Abstract

This paper explores the application of Artificial Intelligence (AI) techniques to enhance the security of Vehicular Cloud Computing. The study begins by examining the unique security concerns in VCC, such as data privacy, authentication, and the potential impact of malicious attacks on safety-critical applications. Traditional security mechanisms face limitations in addressing these challenges due to the complex and dynamic nature of vehicular environments. As a solution, AI techniques, including machine learning, deep learning, and anomaly detection, are proposed to provide adaptive and intelligent security measures. Machine learning algorithms are employed for real-time threat detection and classification, leveraging historical data to recognize patterns indicative of security breaches. Deep learning models, such as neural networks, enhance the accuracy of intrusion detection systems by automatically learning and adapting to evolving threats.