Decentralized Evaluation of Trust in Ad Hoc Networks using Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F22%3A00365364" target="_blank" >RIV/68407700:21240/22:00365364 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9941360" target="_blank" >https://ieeexplore.ieee.org/document/9941360</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/WIMOB55322.2022.9941360" target="_blank" >10.1109/WIMOB55322.2022.9941360</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Decentralized Evaluation of Trust in Ad Hoc Networks using Neural Networks

Popis výsledku v původním jazyce

Trust is an essential concept in ad hoc network security. Creating and maintaining trusted relationships between nodes is a challenging task. This paper proposes a decentralized method for evaluating trust in ad hoc networks. The method uses neural networks and local information to predict the trust of neighboring nodes. The method was compared with the original centralized version, showing that even without global information knowledge, the method has, on average, 97% accuracy in classification and 94% in regression problem. An important contribution of this paper is overcoming the main limitation of the original method, which is the centralized evaluation of trust. Moreover, the decentralized method output is a perfect fit to use as an input to enhance routing in ad hoc networks.

Název v anglickém jazyce

Decentralized Evaluation of Trust in Ad Hoc Networks using Neural Networks

Popis výsledku anglicky

Trust is an essential concept in ad hoc network security. Creating and maintaining trusted relationships between nodes is a challenging task. This paper proposes a decentralized method for evaluating trust in ad hoc networks. The method uses neural networks and local information to predict the trust of neighboring nodes. The method was compared with the original centralized version, showing that even without global information knowledge, the method has, on average, 97% accuracy in classification and 94% in regression problem. An important contribution of this paper is overcoming the main limitation of the original method, which is the centralized evaluation of trust. Moreover, the decentralized method output is a perfect fit to use as an input to enhance routing in ad hoc networks.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

ISBN

978-1-6654-6975-3

ISSN

2160-4886

e-ISSN

2160-4894

Počet stran výsledku

6

Strana od-do

30-35

Název nakladatele

IEEE Computer Society

Místo vydání

USA

Místo konání akce

Thessaloniki (Soluň)

Datum konání akce

10. 10. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000936188900038