A Systematic Review on Intelligent Intrusion Detection Systems for VANETs Vehicular Ad hoc Networks (VANETs) are a growing area that continues to gain interest with an increasing diversity of applications available. These are the underlying network for Intelligent Transportation Systems (ITS), a set of applications and services that aim to provide greater security and comfort to drivers and passengers. However, the characteristics and size of a VANET make it a security challenge. It has been a subject of study, with several research works aimed at this problem, usually involving cryptography. There are, however, some attacks that cannot be solved using traditional methodologies. For example, Sybil attack, Denial of Service (DoS), Black Hole, etc. are not preventable using cryptographic tools. Nonetheless, using an Intrusion Detection System (IDS) can help to detect malicious behavior, preventing further damage. This work presents a Systematic Literature Review (SLR) that aims to evaluate the feasibility of this type of solution. Additionally, it should provide information about the most common approaches, allowing the identification of the most used Machine Learning (ML) algorithms, architectures and datasets.

Evaluation Framework for Network Intrusion Detection Systems for InVehicle CAN Modern vehicles are complex safety critical cyber physical systems, that are connected to the outside world, with all security implications it brings. Different network intrusion detection systems (NIDSs) proposed for the CAN bus, the predominant type of invehicle network, to improve security are hard to compare due to disparate evaluation methods adopted. In this paper we provide the means to compare CAN NIDSs on equal footing and evaluate the ones detailed in the literature. Based on this we observe some limitation of existing approaches and why in the CAN setting it is intrinsically difficult to distinguish benign from malicious payload. We argue that xe2x80x9cmeaningawarexe2x80x9d detection (a concept we define) which is challenging (but perhaps not impossible) to create for this setting.