Lightweight trust model with machine learning scheme for secure privacy in VANET

Muhammad Haleem Junejo; Ab Al Hadi Ab Rahman; Riaz Ahmed Shaikh; Kamaludin Mohamad Yusof; Dileep Kumar; Imran Memon

doi:10.1016/j.procs.2021.10.058

Lightweight trust model with machine learning scheme for secure privacy in VANET

Muhammad Haleem Junejo, Ab Al Hadi Ab Rahman, Riaz Ahmed Shaikh, Kamaludin Mohamad Yusof, Dileep Kumar, Imran Memon

Research output: Contribution to journal › Conference article › peer-review

12 Citations (Scopus)

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Abstract

A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET.

Original language	English
Pages (from-to)	45-59
Number of pages	15
Journal	Procedia Computer Science
Volume	194
Early online date	3 Dec 2021
DOIs	https://doi.org/10.1016/j.procs.2021.10.058
Publication status	Published - 2021
Event	18th International Learning and Technology Conference, L and T 2021 - Virtual, Online, Saudi Arabia Duration: 28 Jan 2021 → …

Keywords

Machine Learning
Trust Model
VANET

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10.1016/j.procs.2021.10.058Licence: CC BY-NC-ND

Junejo_etal_2021_PCSFinal published version, 899 KBLicence: CC BY-NC-ND

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title = "Lightweight trust model with machine learning scheme for secure privacy in VANET",

abstract = "A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET.",

keywords = "Machine Learning, Trust Model, VANET",

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year = "2021",

doi = "10.1016/j.procs.2021.10.058",

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AU - Junejo, Muhammad Haleem

AU - Ab Rahman, Ab Al Hadi

AU - Shaikh, Riaz Ahmed

AU - Yusof, Kamaludin Mohamad

AU - Kumar, Dileep

AU - Memon, Imran

PY - 2021

Y1 - 2021

N2 - A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET.

AB - A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET.

KW - Machine Learning

KW - Trust Model

KW - VANET

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DO - 10.1016/j.procs.2021.10.058

M3 - Conference article

AN - SCOPUS:85121804530

VL - 194

SP - 45

EP - 59

JO - Procedia Computer Science

JF - Procedia Computer Science

SN - 1877-0509

T2 - 18th International Learning and Technology Conference, L and T 2021

Y2 - 28 January 2021

ER -

Lightweight trust model with machine learning scheme for secure privacy in VANET

Abstract

Keywords

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