Black Hole Prevention in VANETs Using Trust Management and Fuzzy Logic Analyzer Nazish Rafique Department of Computer Engineering, CEME, National University of Science and Technology, Islamabad, Pakistan. Muazzam A. khan Department of Computer Engineering, CEME, National University of Science and Technology, Islamabad, Pakistan. Nazar A. Saqib Department of Computer Engineering, CEME, National University of Science and Technology, Islamabad, Pakistan. Faisal Bashir Department of Computer Science, Bahria University, Islamabad, Pakistan. Cory Beard School of Computing & Electrical Engineering, University of Missouri, Kansas City, USA. Zhu Li School of Computing & Electrical Engineering, University of Missouri, Kansas City, USA. Abstract— Vehicular Ad-hoc Networks (VANETs) has gained significant popularity in the field of ICT technology because of its contribution in providing traffic efficiency and road safety to its users. However, in the recent years, researchers have highlighted many security issues that demands attention and effective schemes. These security issues includes many potential attacks that can be launched in VANETs and can degrade the performance of network. This paper aims to discuss one of the security attack called black hole attack in which nodes behaves selfishly and doesn’t cooperate with other nodes in the data transmission phase. It also provides a security framework based on trust management and fuzzy logic analyzer to detect and prevent this attack in future. From the result analysis of simulations we will show the proposed technique enhances network performance and it is the better solution to secure routing protocols and also helps to remove malicious nodes from the network efficiently. Keywords- Vehicular Networks; security attacks; AODV protocol; trust management; black hole attack; fuzzy logic analyzer. I. INTRODUCTION VANETs belongs to that category of ad-hoc networks in which vehicles communicate with other vehicles moving on the road in order to transmit data related to different applications especially to broadcast safety messages [1]. These networks are envisioned to provide an Intelligent Traffic System to solve the problems of current traffic systems like road accidents, traffic congestions and maintenance [2]. Two types of communication takes place in Vehicular Networks: Vehicle-to-Vehicle (V2V), where interact with each other and Vehicle-to-Infrastructure (V2I), where communication takes place between vehicle and Road Side Units (RSU) [3]. Since VANETs provide assistance in real-time emergency applications and also support life critical message exchange between vehicles so that drivers can take right decisions at right time, they must follow the requirements for security for instance: integrity, privacy, non-repudiation and confidentiality to prevent adversaries from manipulating or altering the information sent to other vehicles for safety purposes. The main goal of VANETs should be to provide security and privacy for a secured communication against malicious nodes and attackers [4] [5]. There are various number of attacks in VANETs that can create problems in network for the users to access the system, alter some information or act selfishly in a cooperative environment. These attacks include Man in the Middle, Denial of Service (DoS), Black hole, masquerade, bogus information, worm hole, Illusion attack, Sybil attack, impersonation attack, timing attack and purposeful attack [4]. Among these security attacks, the most severe attack is black hole attack where a selfish node refuses to participate in the data transmission phase. This paper aims to present a technique to mitigate impact of black hole attack using AODV protocol. This technique uses Trust Management and Fuzzy Logic Analyzer to provide a secured communication increasing the performance of network. The remaining paper is organized into following sections: detailed working of AODV protocol is given in Section II. Section III includes the working of black hole attack. Section IV, includes discussion regarding proposed mechanism. II. AODV ROUTING PROTOCOL Adhoc OnDemand Vector protocol belongs to the category of reactive protocols which works on demand basis meaning when there is a requirement of nodes to transmit data to the other nodes within the network. AODV is capable of both multicasting and unicasting. It provides a dynamic network connection and allows to consume less memory and less processing loads. The mechanism of AODV permits nodes to find fresh paths rapidly for new destinations because there is no requirement for nodes to maintain a routing table for destination nodes if they are not in active communication currently. AODV employs destination sequence number for each route entry [6]. AODV routing protocol is divided into three processes: Route Discovery Process, Data Transmission Process, and Route Maintenance Process. Route Discovery Process initiates when a node requires to transfer message to other nodes in the International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 9, September 2016 1226 https://sites.google.com/site/ijcsis/ ISSN 1947-5500