International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol.3, Issue.2, March-April. 2013 pp-1157-1160 ISSN: 2249-6645 www.ijmer.com 1157 | Page V. Geetha Devi, 1 P.Shakeel Ahmed, 2 P.Babu, 3 V. Hemanth Kumar Raju 4 1 M. Tech (CSE), QCET, NELLORE 23 Associate Professor, CSE, QCET, NELLORE 4 Assistant Professor, CSE, NEC, GUDUR Abstract: Security is important for many sensor network applications. A particularly harmful attack against sensor and ad hoc networks is known as the Sybil attack, where a node illegitimately claims multiple identities. In urban vehicular networks, the location privacy of anonymous vehicles is highly concerned and anonymous verification of vehicles is indispensable. Consequently, an attacker who succeeds in forging multiple hostile identifies can easily launch a Sybil attack, gaining excessively large influence. In Vehicular Ad Hoc Networks (VANETs), the vehicular scenario requires smart signaling, smart road maintenance and other services. A brand new security issue is that the semi-trusted Road Side Units (RSUs) may be compromised. The objective of our work is to propose a Threshold ElGamal system based key management scheme for safeguarding VANET from the compromised RSUs and their collusion with the malicious vehicles. By analyzing the packet loss tolerance for security performance demonstration, followed by a discussion on the threshold our method can promote security with low overhead in Emergency Braking Notification and does not increase overhead in and Decentralized Floating Car Data during security promotion. Index Terms: Sybil attack, location privacy, urban vehicular networks, location-hidden trajectory, Signal Strength Distribution, Security I. Introduction Over the past two decades, vehicular networks have been emerging as a cornerstone of the next-generation Intelligent Transportation Systems (ITSs), contributing to safer and more efficient roads by providing timely information to drivers and concerned authorities. In vehicular networks, moving vehicles are enabled to communicate with each other via inter vehicle communications as well as with road-side units (RSUs) in vicinity via roadside-to-vehicle communications. In urban vehicular networks where the privacy, especially the location privacy of vehicles should be guaranteed vehicles need to be verified in an anonymous manner. A wide spectrum of applications in such a network relies on collaboration and information aggregation among participating vehicles. Without identities of participants, such applications are vulnerable to the Sybil attack where malicious vehicle masquerades as multiple identities, overwhelmingly influencing the result. The consequence of Sybil attack happening in vehicular networks can be vital. For example, in safety-related applications such as hazard warning, collision avoidance, and passing assistance, biased results caused by a Sybil attack can lead to severe car accidents. Therefore, it is of great importance to detect Sybil attacks from the very beginning of their happening. Detecting Sybil attacks in urban vehicular networks, however, is very challenging. The First, vehicles are anonymous. There are no chains of trust linking claimed identities to real vehicles. Second, location privacy of vehicles is of great concern. Location information of vehicles can be very confidential. For example, it can be inferred that the driver of a vehicle may be sick from knowing the vehicle is parking at a hospital. It is inhibitive to enforce a one-to-one correspondence between claimed identities to real vehicles by verifying the physical presence of a vehicle at a particular place and time. Third, conversations between vehicles are very short. Due to high mobility of vehicles, a moving vehicle can have only several seconds to communicate with another occasionally encountered vehicle. It is difficult to establish certain trustworthiness among communicating vehicles in such a short time. This makes it easy for a malicious vehicle to generate a hostile identity but very hard for others to validate. Furthermore, short conversations among vehicles call for online Sybil attack detection. The detection scheme fails if a Sybil attack is detected after the attack has terminated. Fig. 1: Vehicular networks A Route map for Detecting Sybil Attacks in Urban Vehicular Networks