Blackhole Attack and its effect on VANET
DOI:
https://doi.org/10.26438/ijcse/v5i11.2532Keywords:
Blackhole Attack Detection, AODV, Neighborhood based blackhole detection, Sequence Number based blackhole detection, Packet Drop rate based blackhole detection, Cluster Forming based blackhole detectionAbstract
VANET is one type of adhoc networks which established among vehicles equipped with communication facilities. In VANETs vehicles are equipped with device known as on Board Unit (OBU) through which it can communicate with other vehicles as well as with infrastructure which is known as Road Side Unit (RSU). VANET can be used for different applications like Life-Critical Safety Applications, Safety warning Applications, Electronic Toll Collections, Internet Access in vehicles, Vehicle Group Communications, Roadside Services Finder and many more. Various researchers are proposing different solutions in VANET for Protocols, Effective Service Parameters, Smart Network challenges and lot more by seeing the usefulness of VANETs in various applications but security is a main issue for adopting VANET as a life critical solution. Security is the major concern for various VANET applications where a wrong, replicated or delayed messages may directly or indirectly affect the human lives. Many of the applications require a high level of security in VANET adoption. Security Attacks on VANET can be categories in Routing Attack, Monitoring Attack, Social Attack, Timing Attack, Application Attack and Network Attack. In this paper we focused on Routing Attack detection, specifically Blackhole Attack detection methodologies. We have proposed four different approaches for Blackhole attack detection: Neighborhood based, Sequence Number based, Packet Drop rate based and Cluster Forming based. We analyze the performance of the proposed approaches for different scenario with comparative analysis.
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