An Adaptive Cluster based Vehicular Routing Protocol for Secure Communication

Divya, N. Sree; Bobba, Veeramallu; Vatambeti, Ramesh

doi:10.1007/s11277-021-08717-4

Cited by 8 publications

(5 citation statements)

References 26 publications

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“…The distributed ledger contains a record of every transaction that has been validated. Equation (15) provides the MAE: 15) where n represents the total sum of users and 𝑋𝑋 𝑖𝑖 represents the individual costs of communicating with and making a transaction with each user. Some specialised security attacks pose a threat to data providers if their customers' personal information is shared.…”

Section: Communication With Diagnosed Patientsmentioning

confidence: 99%

“…14 Deep neural networks (DNNs) can identify malfunctions in virtualized communication networks with greater precision by learning to recognize typical data flows and rebuilding them. 15 However, a significant challenge with these models is that sophisticated DNNs in the core clouds require more time to train than currently available classical approaches. Therefore, finding new ways to reduce training time without sacrificing detection precision is essential.…”

Section: Introductionmentioning

confidence: 99%

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Securing the patient healthcare data using Deep Inception-ResNet based CPABPP model in Internet of Things

Reddy,

Baswaraju,

Kumari

et al. 2024

JIST

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The IoT is transforming healthcare by enabling extensive connectivity between medical professionals, equipment, staff, and patients, facilitating real-time monitoring. While the network's scale and diversity offer advantages for data exchange, they also pose challenges for privacy and security, particularly with sensitive medical information. To address this, deep learning-based cryptographic and biometric systems are utilized for authentication and anomaly detection in medical systems. However, power constraints on network sensors necessitate efficient security schemes. Thus, the authors propose a novel framework, the deep Inception-ResNetV2 with privacy preservation, to secure data transmission while minimizing encryption and decryption time. Implementing this method reduces the network's burden, saving time and costs in communication. Compared to alternatives like private biometric-based authentication, this model demonstrates superior performance.

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Section: Communication With Diagnosed Patientsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Securing the patient healthcare data using Deep Inception-ResNet based CPABPP model in Internet of Things

Reddy,

Baswaraju,

Kumari

et al. 2024

JIST

View full text Add to dashboard Cite

show abstract

“…In (Divya, et al, 2021), the authors proposed a Clustered Vehicle Location scheme using Hybrid Krill Herd and Bat Optimization (CVL-HKH-BO) method to detect and prevent black hole and wormhole attacks using an appropriate fitness function. For improving energy consumption and packet delay, the authors used the CVL method.…”

Section: Related Workmentioning

confidence: 99%

Rvmf: Reliable Routing Method for Vehicular Ad Hoc Networks Using Moth-Flame and Firefly Optimization Algorithms

Pasha

2023

SJUOZ

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With the advancement of wireless communication technology, the intelligent transportation system (ITS) has attracted the attention of vehicle companies and academic researchers. Recently, vehicular ad hoc networks (VANETs) as a leading genuine technology have received serious attention as a kind of mobile ad hoc network (MANET) to ensure the safety of vehicles, drivers, and passengers. However, these networks face many challenges due to the mobility of vehicle nodes, wireless communication, and frequent topology changes. One of the crucial issues of these networks is a cluster-based routing scheme with the ability to provide quality of service (QoS) parameters. A clustering scheme is an appropriate method for increasing the scalability of VANETs. In a cluster-based routing scheme, the cluster head (CH) is responsible for receiving data from its member nodes, and aggregating and transferring data to the next CH node. On the other hand, providing a suitable clustering method is NP-hard problems and meta-heuristic algorithms are suitable for solving these problems. A scalable and reliable routing scheme is necessary and essential in VANETs. In this paper, a routing method based on the clustering technique is presented considering the moth-flame optimization (MFO) algorithm for clustering and the Firefly optimization algorithm (FoA) with a suitable fitness function for routing between CHs. The simulation of the proposed method with MATLAB software shows that the proposed RVMF method improves the parameters of packet delivery rate (PDR), latency, and throughput.

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“…Particular attention is paid in this essay to the RPL protocol, which is vulnerable to routing attacks. Attacks against RPL may be broken down into two groups: those that are carried over from WSNs and those that are special to RPL and take advantage of its particular weaknesses [9]. This page details a variety of RPL assaults, such as Flood Attacks, Data-DoS/DDoS Attacks [10], which mostly target layer 3 of the OSI perfect.…”

Section: Introductionmentioning

confidence: 99%

Routing Attack Detection Using Ensemble Deep Learning Model for IIoT

Vatambeti¹,

Mamidisetti²

2023

IDA

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Smart cities, ITS, supply chains, and smart industries may all be developed with minimal human interaction thanks to the increasing prevalence of automation enabled by machine-type communication (MTC). Yet, MTC has substantial security difficulties because of diverse data, public network access, and an insufficient security mechanism. In this study, we develop a novel IIOT attack detection basis by joining the following four main steps: (a) data collection, (b) pre-processing, (c) attack detection, and (d) optimisation for high classification accuracy. At the initial stage of processing, known as "pre-processing," the collected raw data (input) is normalised. Attack detection requires the creation of an intelligent security architecture for IIoT networks. In this work, we present a learning model that can recognise previously unrecognised attacks on an IIoT network without the use of a labelled training set. An IoT network intrusion detection system-generated labelled dataset. The study also introduces a hybrid optimisation algorithm for pinpointing the optimal LSTM weight when it comes to intrusion detection. When trained on the labelled dataset provided by the proposed method, the improved LSTM outperforms the other models with a finding accuracy of 95%, as exposed in the research.

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An Adaptive Cluster based Vehicular Routing Protocol for Secure Communication

Cited by 8 publications

References 26 publications

Securing the patient healthcare data using Deep Inception-ResNet based CPABPP model in Internet of Things

Securing the patient healthcare data using Deep Inception-ResNet based CPABPP model in Internet of Things

Rvmf: Reliable Routing Method for Vehicular Ad Hoc Networks Using Moth-Flame and Firefly Optimization Algorithms

Routing Attack Detection Using Ensemble Deep Learning Model for IIoT

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