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Title	A Novel Mechanism For Misbehavior Detection In Vehicular Networks
ID_Doc	3437
Authors	Valentini E.P.; Filho G.P.R.; De Grande R.E.; Ranieri C.M.; Pereira L.A.; Meneguette R.I.
Year	2023
Published	IEEE Access, 11
DOI	http://dx.doi.org/10.1109/ACCESS.2023.3292055
Abstract	Intelligent Transport Systems (ITS) have provided new technologies to protect human life, speed up assistance, and improve traffic, to aid drivers, passengers, and pedestrians. Vehicular Ad-hoc Networks (VANET) are the fundamental elements in an ITS ecosystem. However, its characteristics make the system susceptible to numerous attacks, such as Denial of Service (DoS). In this paper, we proposed a security system based on intrusion detection called Detection of Anomalous Behaviour in Smart Conveyance Operations (DAMASCO). We used a statistical approach to detect anomalies in vehicle-to-vehicle communication (V2V). The anomaly detection module addresses the Medium Access Control (MAC) sublayer to assess the number of packages sent to identify potentially malicious nodes, block their activity, and maintain a reputation list. The algorithm calculates the Median Absolute Deviation (MAD) to identify outliers and characteristics of DoS. Our experiments were performed in a simulated environment using a realistic urban mobility model. The results demonstrate that the proposed security system achieved a 3% false positive rate and no false negatives. © 2013 IEEE.
Author Keywords	Cyber attacks; denial of service; Internet of Things; intrusion detection; smart cities; vehicular networks

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