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- W2911673112 abstract "Background: The blackhole infection can affect the collaborative communication in mobile networks. It is man-in-middle attack that seizes and deflects the route and avoids packet-forwarding in the network. The occurrence of collaborative-blackhole reduces the trust and trustworthiness over the network. Objective: A probabilistic and weighted analysis based protocol is proposed in this research for detection of cooperative blackhole nodes and generating the preventing route over the network. The aim of the work is to improve the communication reliability. Methods: In this paper, the communication behaviour is analyzed under associated and probabilistic measures using Data Routing Information (DRI) table to discover the blackhole attack. It applies a dual check 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 a comprehensive evaluation within the proposed PSAODV (Probabilistic Secure Adhoc On Demand Distance Vector) protocol. Results: The simulation of PSAODV protocol is conducted in NS2 environment on various scenarios with mobility, density and traffic type variations. The scenarios are defined with a higher density of blackhole nodes within the network. The adaptive weights are identified by simulating the network with different weight combinations. These weights are employed within the PSAODV protocol to configure it with the maximum benefits. The analytical evaluations are taken against AODV and SAODV protocols and identified the performance enhancement in terms of Packet Delivery Ratio (PDR) Ratio, delay, attack detection ratio parameters. Conclusion: A significant improvement in attack detection is achieved by this proposed PSAODV protocol. The proposed protocol improved the reliability and effectiveness of mobile network." @default.
- W2911673112 created "2019-02-21" @default.
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- W2911673112 date "2020-02-07" @default.
- W2911673112 modified "2023-10-18" @default.
- W2911673112 title "DRI Table Based Traffic-Behaviour Analysis Approach for Detection of Blackhole Attack" @default.
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- W2911673112 doi "https://doi.org/10.2174/2210327909666190208154847" @default.
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