A Comprehensive Survey on Anomaly Detection Techniques in VANETs: Challenges and Opportunities

Manne Naga Chandra Sekhar Chowdhary, Rohan Satya Bandaru Balaji, S Sreenivasa Chakravarthi, S Sountharrajan

2025

Abstract

The emergence and development of Vehicular Ad Hoc Networks (VANETs) as part of Intelligent Transportation Systems (ITS) bring with them critical operational challenges, with security being paramount. Among these, the detection of anomalies stands out as a vital task to ensure the smooth functioning of VANET communication. Anomaly detection, leveraging advanced machine learning (ML) and deep learning (DL) techniques, has emerged as a vital solution to address these challenges. This paper presents a comprehensive survey of recent developments in anomaly detection methods for VANETs. It investigates the supervised, unsupervised, and hybrid learning techniques of CNNs and LSTM networks and federated learning models for anomaly identification in various scenarios. Furthermore, benchmark datasets such as KDD99, NSL-KDD, and VeReMi are reviewed for evaluating the efficacy of these methods. This survey discusses the strengths, weaknesses, and emerging trends within anomaly detection. One such trend is collaborative and privacy-preserving frameworks for anomaly detection. The current work aims to provide guidance for future research in finding robust and real-time anomaly detection systems, thus ensuring the security and reliability of VANETs in environments of increasing complexity.

Paper Citation

in Harvard Style

Chowdhary M., Balaji R., Chakravarthi S. and Sountharrajan S. (2025). A Comprehensive Survey on Anomaly Detection Techniques in VANETs: Challenges and Opportunities. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 644-655. DOI: 10.5220/0013583200004664

in Bibtex Style

@conference{incoft25,
author={Manne Naga Chandra Sekhar Chowdhary and Rohan Satya Bandaru Balaji and S Sreenivasa Chakravarthi and S Sountharrajan},
title={A Comprehensive Survey on Anomaly Detection Techniques in VANETs: Challenges and Opportunities},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={644-655},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013583200004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - A Comprehensive Survey on Anomaly Detection Techniques in VANETs: Challenges and Opportunities
SN - 978-989-758-763-4
AU - Chowdhary M.
AU - Balaji R.
AU - Chakravarthi S.
AU - Sountharrajan S.
PY - 2025
SP - 644
EP - 655
DO - 10.5220/0013583200004664
PB - SciTePress