Next-Generation Systems and Secure Computing

9Enhanced Security Measures Within the ITS Infrastructure Through the Application of Machine Learning Algorithms for Anomaly Detection

Shiplu Das^1*, Soumi De², Ananya Ghosh², Sovraj Dey² and Tania Bhattacharjee²

¹Department of Computer Science and Engineering, Adamas University, West Bengal, India

²Department of Computer Science and Engineering, Brainware University, West Bengal, India

Abstract

Intelligent Transportation Systems (ITSs) have been advancing in recent years, improving traffic management, vehicular accidents, congested roads, etc. This study proposes the open nature of ITS as a wireless technology, considering its security and privacy challenges. Scalability, privacy, computational cost, communication overhead, latency, and other types of security assaults have all been considered when categorizing security and privacy methods in ITS and their limits. This collaborative approach, based on group feedback, is advantageous for creating a transport system for the future. In this study, using techniques such as Machine Learning, Traffic simulation, and Anonymization, the work of ITS is enhanced. This poll has identified several issues with intelligent transport systems and has suggested crowd-intelligent remedies. This study explored the application of machine-learning algorithms for anomaly detection in ITS to detect and mitigate potential security breaches and abnormal activities. By analyzing vast amounts of data collected from various ITS components, machine learning ...