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DRI Table based Traffic-Behaviour Analysis Approach for Detection of Blackhole Attack


Kapil Juneja*  


The blackhole infection can affect the collaborative communication in mobile networks. In this paper, the communication behaviour is analyzed under associated and probabilistic measures using DRI table to discover the blackhole attack. A dual check is applied based on participation and communication constraints to estimate the node-criticality. The evaluation is performed by neighbours and neighbour-on-neighbour nodes with weights and threshold specific decisions. These measures are evaluated through composite and integrated measures and presented as decision metrics. The parametric and probabilistic checks are conducted as inclusive evaluation within the proposed PSAODV (Probabilistic Secure AODV) protocol. The simulation of PSAODV protocol is conducted in NS2 environment on multiple scenarios with mobility, density and traffic type variations. The scenarios are defined with higher density of blackhole nodes within the network. The adaptive weights are identified by simulating the network with different weight combinations. These weights are applied within the PSAODV protocol to configure it with maximum benefit. The analytical evaluations are taken against AODV and SAODV protocols and identified the performance enhancement in terms of PDR Ratio, delay, attack-detection ratio parameters. A significant improvement in attack detection is achieved by this proposed PSAODV protocol.


Mobile Network, AODV, DRI, Blackhole Attack, Probabilistic


Department of Computer Science and Engineering, University Institute of Engineering and Technology, Maharshi Dayanand University, Rohtak, Haryana,124001

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