TREE: Trust-Based Authenticated and Secure Dissemination of Emergency Event Information for the Network of Connected Vehicles

Tripathi, Kuldeep Narayan; Yadav, Ashish Mohan; Sharma, Subhash C.

doi:10.1007/s13369-022-06753-1

Cited by 11 publications

(7 citation statements)

References 55 publications

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“…In the above equation the coordinates of the sender and receiver are represented as (

{Y}_R-{Z}_R

) and

\left({Y}_S-{Z}_S\right)

, respectively 22 …”

Section: Proposed Designmentioning

confidence: 99%

See 1 more Smart Citation

An optimal trust and secure model using deep metric learning for fog‐based VANET

Tripathi¹,

Sharma

2023

Trans Emerging Tel Tech

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Vehicular ad hoc network (VANET) is a technique that enhances road safety via communication between two different vehicles. Trust establishment in VANET in between the vehicles is the most significant factor that provides secure reliability and integrity. Reliability and trust assist the vehicles in gathering credible data from neighboring vehicles. On the other hand, incomplete and inaccurate data gathered by the vehicles contain interrupting effect on VANET. Therefore, this article proposes a modified deep metric learning‐based chaotic Henry gas solubility optimization (MDML‐CHGSO) approach to provide a trust‐based security design. The proposed trust model is based on plausibility as well as experience in securing vehicle networks. The proposed model verifies the received data's genuineness from the approved vehicle using various processes namely, authentication, lifetime verification, experience evaluation, plausibility determination, and accurate measurement. The adoption of the modified DML‐based CHGSO approach extracts the location of the event message accurately when the location of the message is located closer to the fog nodes. In addition to this, average latency, throughput and packet delivery ratio, are the metrics evaluated for rating the performance.

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“…In the above equation the coordinates of the sender and receiver are represented as (

{Y}_R-{Z}_R

) and

\left({Y}_S-{Z}_S\right)

, respectively 22 …”

Section: Proposed Designmentioning

confidence: 99%

“…In the above equation the coordinates of the sender and receiver are represented as (Y R − Z R ) and (Y S − Z S ), respectively. 22 Node R uses the below equation to calculate the D RSS to node S through node M.…”

Section: Distance-based Location Verificationmentioning

confidence: 99%

An optimal trust and secure model using deep metric learning for fog‐based VANET

Tripathi¹,

Sharma

2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…Any robotic network made with compromised bot or machine running a malicious software using the command driven by a botmaster is other named a Botnet [58]. It is a malicious act with damaging intentions carried out on IOT devices and IOT networks to achieve various purposes such as keylogging attack, email spam delivery, distributed denial of services attack, cryptocurrency attack, password cracking [7][37].…”

Section: The Botnet Atackmentioning

confidence: 99%

Securing the Perceptual Layer of the Internet of Things (Iot) Devices Using Elliptic Curve Cryptography

Okediran

Vincent

Abayomi‐Alli

et al. 2023

Preprint

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The security of IOT layers has become very important considering the various attacks faced by IOT devices especially, the perceptual layer. Reported attacks in recent times include direct Denial of Service (DDoS), Botnet attack and Falsification attacks. Several security techniques in place can not be directly implemented on IOT devices; hence, there is a need to improve the research.This work has proposed an ECC based on binary field solution, there were three stages of implementation which includes device registration where each devices are recognised and locked against all forms of communication, device authentication for key agreement and unlocking, communication phase for exchange of information. It was implemented on a contactless ATM card and a mobile phone as an IOT devices used for electronic payment. The evaluation result for storage capacity showed that the mobile phone and the ATM card has the capacity to run ECC security protocol directly, the Jitter result obtained reveals that the Jitter value did not deviate from normal for both devices while, the computational time showed that it is computationally efficient to use ECC over binary field for the security of the perceptual layer.

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“…TREE. In the publication denoted as [77], the authors have formulated a trust-based message propagation scheme for a vehicular network for the purpose of discerning the issue of fraudulent nodes transmitting spurious alarm messages. Initially, they have contrived a trust-based mechanism to assess the credibility of the node through the node's message transmission pace and event notifcation execution to validate the veritable emergency warning messages.…”

Section: Saodv (Secure Ad-hoc On-demand Distance Vector)mentioning

confidence: 99%

Investigation of Different Mechanisms to Detect Misbehaving Nodes in Vehicle Ad-Hoc Networks (VANETs)

Nobahari,

Bakhshayeshi Avval,

Akhbari

et al. 2023

Security and Communication Networks

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The vehicle ad-hoc network (VANET) is a crucial technology that will play a significant role in shaping the future of transition systems, which is widely used as a subset of ad-hoc networks. VANET aims to ensure driver safety by establishing independent communication with nearby vehicles. A key requirement for successful data transmission is cooperation among nodes, as factors such as high mobility, limited radio range, signal fading, and noise lead to packet loss. Security issues in vehicle ad-hoc networks have recently become a major concern. One factor that affects security is the presence of abusive nodes in the network. Like selfish nodes, they are reluctant to share their sources with their neighbors and try to keep their property. The misbehavior of malicious nodes includes dissemination of false traffic information, false location information, and redirection of packets to a wrong path, retransmission of packets, impersonation, so these nodes should be tracked down to ensure the operation of the network. This article provides a complete summary of various research works proposed to detect selfish and malicious nodes and isolate them from honest vehicles. This review article first describes the types of attacks. It then presents the methods proposed by researchers to deal with uncooperative nodes and compares their performance based on parameters such as the number of misbehaving nodes detected, overhead, throughput, layer involved in the attacks.

show abstract

TREE: Trust-Based Authenticated and Secure Dissemination of Emergency Event Information for the Network of Connected Vehicles

Cited by 11 publications

References 55 publications

An optimal trust and secure model using deep metric learning for fog‐based VANET

An optimal trust and secure model using deep metric learning for fog‐based VANET

Securing the Perceptual Layer of the Internet of Things (Iot) Devices Using Elliptic Curve Cryptography

Investigation of Different Mechanisms to Detect Misbehaving Nodes in Vehicle Ad-Hoc Networks (VANETs)

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