Performance Analysis of Neural Network Approach for Evaluation of Trust in Ad-Hoc Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F21%3A00351927" target="_blank" >RIV/68407700:21240/21:00351927 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/9548546" target="_blank" >https://ieeexplore.ieee.org/document/9548546</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACIT52158.2021.9548546" target="_blank" >10.1109/ACIT52158.2021.9548546</a>

Result language

angličtina

Original language name

Performance Analysis of Neural Network Approach for Evaluation of Trust in Ad-Hoc Networks

Original language description

With the world becoming more mobile and dynamic each year, the application of ad-hoc networks has broadened. Ad-hoc networks do not have a predefined infrastructure; each node serves as a router, bringing security challenges. Trust and trustworthiness mechanisms are among the most common methods for ensuring security in an ad-hoc network. In [1], we proposed a method for the evaluation of trust in ad-hoc networks. This paper aims to describe the method formally and analyze its performance. The original paper showed that neural networks could do trust estimation with an average 98% accuracy of the classification and 94% of the regression problem. This paper aims to investigate the capabilities of our method under malicious conditions. The analysis could also provide insight for tuning trust parameters, such as the threshold of trust. Furthermore, this paper presents a mathematical model behind the problem to show that the neural network approach is reasonable.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

11th International Conference on Advanced Computer Information Technologies (ACIT)

ISBN

978-1-6654-1854-6

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

691-695

Publisher name

IEEE (Institute of Electrical and Electronics Engineers)

Place of publication

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Event location

Deggendorf

Event date

Sep 15, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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