TELKOMNIKA Telecommunication, Computing, Electronics and Control
Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network
Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network
Subject
Artificial intelligence
Communication security
Cyber security
IoT
Network
Security
Smart car
Trust management reputation
Communication security
Cyber security
IoT
Network
Security
Smart car
Trust management reputation
Description
High reliance on wireless network connectivity makes the vehicular ad hoc
network (VANET) vulnerable to several kinds of cyber security threats.
Malicious vehicles accessing the network can lead to hazardous situation by
disseminating misleading information or data in the network or by
performing cyber-attacks. It is a requirement that the information must be
originated from the authentic and authorized vehicle and confidentiality must
be maintained. In these circumstances, to protect the network from malicious
vehicles, reputation system based on beta probability distribution with trust
management model has been proposed to differentiate trustworthy vehicles
from malicious vehicles. The trust model is based on adaptive neuro fuzzy
inference system (ANFIS) which takes trust metrics as input to evaluate the
trustworthiness of the vehicles. The simulation platform for the model is in
MATLAB. Simulation results show that the vehicles need at least 80%
trustworthiness to be considered as a trusted vehicle in the network.
network (VANET) vulnerable to several kinds of cyber security threats.
Malicious vehicles accessing the network can lead to hazardous situation by
disseminating misleading information or data in the network or by
performing cyber-attacks. It is a requirement that the information must be
originated from the authentic and authorized vehicle and confidentiality must
be maintained. In these circumstances, to protect the network from malicious
vehicles, reputation system based on beta probability distribution with trust
management model has been proposed to differentiate trustworthy vehicles
from malicious vehicles. The trust model is based on adaptive neuro fuzzy
inference system (ANFIS) which takes trust metrics as input to evaluate the
trustworthiness of the vehicles. The simulation platform for the model is in
MATLAB. Simulation results show that the vehicles need at least 80%
trustworthiness to be considered as a trusted vehicle in the network.
Creator
Dilshad Ara Hossain, S. M. Salim Reza
Source
http://journal.uad.ac.id/index.php/TELKOMNIKA
Date
Apr 22, 2021
Contributor
peri irawan
Format
pdf
Language
english
Type
text
Files
Collection
Citation
Dilshad Ara Hossain, S. M. Salim Reza, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network,” Repository Horizon University Indonesia, accessed September 20, 2024, https://repository.horizon.ac.id/items/show/4204.
Malicious vehicle detection based on beta reputation and trust management for secure communication in smart automotive cars network,” Repository Horizon University Indonesia, accessed September 20, 2024, https://repository.horizon.ac.id/items/show/4204.