An Efficient multi stage security model based on cross layer mechanism for identifying and preventing black hole attack in wireless ad-hoc networks
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2018-05-29 https://doi.org/10.14419/ijet.v7i2.31.13445 -
Mobile adhoc network, cross layer, malicious attacks, blackhole attack, security in wireless adhoc networks. -
Abstract
Mobile Adhoc Network (MANET) is one of the popular and highly demanded networks functioning under wireless adhoc network. It has high demand by various emerging applications in the entire world. MANET and its necessities are increasing day by day. MANET and its various components like node, route and etc., are too dynamic regarding creating, deployment, mobility, speed, join and disconnect from the network. MANET does not require any existing infrastructure whereas it starts functions in any place at any time. Due these reasons various malicious activities are created dynamically and it degrades the performance of the network. This paper focused on detecting and identifying malicious activities one who affects the data directly. Such kind of malicious activity is blackhole attack where it destroys the data during transmission in a route. In order to detect and eliminated blackhole attack this paper focused on monitoring and investigating various functionalities of the network using a Multi Stage Security Model (MSSM). The MSSM is used for detecting and preventing blackhole attacks in MANET which involves investigating cross layer functionalities during data transmission. And it also investigates and analyzes the entire information that is available in the network. This proposed MSSM is simulated in Network Simulation-2 software and the results are verified and the performance is evaluated.
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How to Cite
Jagadeesan, S., & Parthasarathy, V. (2018). An Efficient multi stage security model based on cross layer mechanism for identifying and preventing black hole attack in wireless ad-hoc networks. International Journal of Engineering & Technology, 7(2.31), 212-218. https://doi.org/10.14419/ijet.v7i2.31.13445Received date: 2018-05-29
Accepted date: 2018-05-29
Published date: 2018-05-29