Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/331807
Title: | Selfish Nodes Mitigation Mechanism Through Trust Management Framework In Wireless Sensor Network |
Researcher: | Kanchana Devi, V |
Guide(s): | Ganesan, R |
Keywords: | Computer Science Computer Science Artificial Intelligence Engineering and Technology |
University: | VIT University |
Completed Date: | 2019 |
Abstract: | Wireless Sensor Network (WSN) consists of sensor nodes, which are deployed in newlinean open environment for monitoring physical phenomena and transmit data to the sinknode through multi-hop communication which is vulnerable for inside and outside attackers.The traditional cryptographic security mechanisms can be compromised by newlinethe attacker. Trust Management bridges the gap laid by the traditional security mechanisms.Reputation based trust management is a powerful system which can be deployed for mitigating the inside attacker and improve the trust between the nodes in an open remote unattended environment. Consecutive dropping of the packets and the early detection of the selfish nodes are some of the challenges that demand attention to improve robustness in WSN. The primary objective of this research work is to propose a selfish node mitigation mechanism using trust management, as follows: _ A reputation based framework to identify and isolate the selfish node in WSN._ A novel algorithm for mitigation of selfish nodes by watching the neighbor node and addressing the consecutive drops. Formulation of the trust value of each node through the Beta Probability Distribution Function. Applying the calculated trust in Semi-Markov Process inspired model for statechange and isolating the corresponding selfish node. Simulation experiments were carried out using the Network Simulator (Version 2.35). The performance of the wireless sensor network was analyzed by varying the number of sensor nodes and selfish nodes, considering various network performance metrics like network lifetime, throughput, energy, and packet delivery ratio. Simulation results depicted the proposed framework as highly efficient in detecting and isolating the selfish nodes when compared to various approaches considered for the analysis. newline |
Pagination: | i-x, 102 |
URI: | http://hdl.handle.net/10603/331807 |
Appears in Departments: | School of Computing Science and Engineering -VIT-Chennai |
Files in This Item:
File | Description | Size | Format | |
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01_title page.pdf | Attached File | 165.84 kB | Adobe PDF | View/Open |
02_declartion & certifigate.pdf | 2.12 MB | Adobe PDF | View/Open | |
03_abstract.pdf | 89.44 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 61.84 kB | Adobe PDF | View/Open | |
05_table of contents.pdf | 210.07 kB | Adobe PDF | View/Open | |
06_list of figures.pdf | 99.14 kB | Adobe PDF | View/Open | |
07_list of tables.pdf | 63.52 kB | Adobe PDF | View/Open | |
08_list of terms and abbreviations.pdf | 108.03 kB | Adobe PDF | View/Open | |
09_chapter_01.pdf | 1.65 MB | Adobe PDF | View/Open | |
10_chapter_02.pdf | 1.77 MB | Adobe PDF | View/Open | |
11_chapter_03.pdf | 327.62 kB | Adobe PDF | View/Open | |
12_chapter_04.pdf | 777.73 kB | Adobe PDF | View/Open | |
13_chapter_05.pdf | 1.22 MB | Adobe PDF | View/Open | |
14_chapter_06.pdf | 952.02 kB | Adobe PDF | View/Open | |
15_chapter_07.pdf | 970.59 kB | Adobe PDF | View/Open | |
16_chapter_08.pdf | 108.76 kB | Adobe PDF | View/Open | |
17_bibliography.pdf | 311.85 kB | Adobe PDF | View/Open | |
18_list of publications.pdf | 94.33 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 274.99 kB | Adobe PDF | View/Open |
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