1 research outputs found
Detecting Sybil Attacks in Vehicular Ad Hoc Networks
Ad hoc networks is vulnerable to numerous number of attacks due to its
infrastructure-less nature, one of these attacks is the Sybil attack. Sybil
attack is a severe attack on vehicular ad hoc networks (VANET) in which the
intruder maliciously claims or steals multiple identities and use these
identities to disturb the functionality of the VANET network by disseminating
false identities. Many solutions have been proposed in order to defense the
VANET network against the Sybil attack. In this research a hybrid algorithm is
proposed, by combining footprint and privacy-preserving detection of abuses of
pseudonyms (P2DAP) methods. The hybrid detection algorithm is implemented using
the ns2 simulator. The proposed algorithm is working as follows, P2DAP acting
better than footprint when the number of vehicles increases. On the other hand,
the footprint algorithm acting better when the speed of vehicles increases. The
hybrid algorithm depends on encryption, authentication and on the trajectory of
the vehicle. The scenarios will be generated using SUMO and MOVE tools