Anglia Ruskin Research Online (ARRO)
Browse

File(s) not publicly available

Route optimasation based on multidimensional trust evaluation model in mobile ad hoc networks

conference contribution
posted on 2023-07-26, 13:56 authored by Antesar Shabut, Keshav P. Dahal, Irfan U. Awan, Zeeshan Pervez
With the increased numbers of mobile devices working in an ad hoc manner, there are many problems in secure routing protocols. Finding a path between source and destination faces more challenges in Mobile ad hoc network (MANET) environment because of the node movement and frequent topology changes, besides, the dependence on the intermediate nodes to relay packets. Therefore, trust technique is utilised in such environment to secure routing and stimulate nodes to cooperate in packet forwarding process. In this paper, an investigation of the use of trust to choose the optimised path between two nodes is provided. It comes up with a proposal to select the most reliable path based on multidimensional trust evaluation technique to include number of hubs, trust opinion, confidence in providing trust, and energy level of nodes on the path. The model overcomes the limitation of considering only trustworthiness of the nodes on the path and uses a route optimisation approach to select the path between source and destination. The empirical analysis shows robustness and accuracy of the trust model in a dynamic MANET environment.

History

Page range

28-34

Publisher

IEEE

Place of publication

Online

Title of book

2015 Second International Conference on Information Security and Cyber Forensics (InfoSec)

ISBN

978-1-4673-6988-6

Conference proceeding

2015 Second International Conference on Information Security and Cyber Forensics (InfoSec)

Name of event

2015 Second International Conference on Information Security and Cyber Forensics (InfoSec)

Location

Cape Town, South Africa

Event start date

2015-11-15

Event finish date

2015-11-17

Language

  • other

Legacy posted date

2016-10-12

Legacy creation date

2016-09-29

Legacy Faculty/School/Department

ARCHIVED Faculty of Science & Technology (until September 2018)

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC