Contribution/Originality: This study is one of the very few studies which have investigated security and privacy issues in VANET. We carried out a selective review of published work on this field between 2003 and 2015; and based on our findings, derived a new perspective, and categorized the security attacks on this type of network. 1. INTRODUCTION Vehicular Ad-Hoc Networks (VANETs) is an extension of Mobile Ad-Hoc Networks (MANETs). In Vehicular Ad-hoc Networks (VANETs), wireless-equipped vehicles form a network spontaneously while traveling along the road. Direct wireless transmission from vehicle to vehicle makes it possible to communicate even where there is no telecommunication infrastructure, such as base stations or access points of wireless dedicated access networks; vehicles can share up-to-date traffic information on the fly [1]. This is an emerging new technology to integrate the capabilities of new generation wireless networks to vehicles. The idea is to provide ubiquitous connectivity to vehicular nodes while on the move, and create efficient vehicle-to-vehicle communications that enable the Intelligent Transportation Systems (ITS) [2]. The network is based on node to node communication. A node can either be a user (vehicle) who desires certain information, or a Road Side Unit (RSU). The node, be it vehicles or RSU, can communicate and exchange data for purposes of information inquiry or distribution. The ultimate goal of VANETs is to enhance the driving experience and increase the level of safety for drivers [3-6]. This is achieved by allowing nodes within certain ranges to

Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.