Malicious Node Detection in Wireless Sensor Networks Using an Efficient Secure Data Aggregation Protocol

Gomathi, S.; Krishnan, C. Gopala

doi:10.1007/s11277-020-07291-5

Cited by 24 publications

(8 citation statements)

References 14 publications

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“…Further, in the proposed scheme, the energy consumption was minimized using sensor grouping technique. A new data aggregation protocol [20] was presented by Gomathi et al in 2020. In this work, tree topology was utilized to provide a logical group.…”

Section: Literature Reviewmentioning

confidence: 99%

An Iterative Convolutional Neural Network Based Malicious Node Detection (ICNN-MND) Protocol For Internet of Things

Moka

Serome

Rajalakshmi

2023

Preprint

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At present Internet of Things (IoT) is widely used in various products and parts in our daily life. In the future, its uses and requirements will increase. However, there are several issues with the IoT network, one of which is secure data transmission. Also, malicious nodes in the IoT network are very difficult to identify accurately and quickly, whereas it is very important to do so. In the current context, several solutions are being proposed as there is a need to focus on setting up secure IoT frameworks, and as well as the protocols that runs on them. This research proposes a secure protocol called iterative Convolutional Neural Network based Malicious Node Detection (ICNN-MND) protocol that uses the erroneous assumption learning problematic technique. This protocol will make changes in the application layer, the network layer and the physical layer in order to achieve secure data transmission in IoT. The proposed IC-MND protocol will be able to detect attacks and eliminate them hence providing maximum data accuracy in IoT. For this, machine learning method will be used and the changes in the characteristics of the malicious nodes will be learned and their boundaries be explored. Then its error variation will be calculated and the malicious nodes be differentiated.

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Section: Literature Reviewmentioning

confidence: 99%

An Iterative Convolutional Neural Network Based Malicious Node Detection (ICNN-MND) Protocol For Internet of Things

Moka

Serome

Rajalakshmi

2023

Preprint

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“…Yu et al 32 studied DNA barcoding and some related technologies to improve knowledge about plant identification and identification over the last 10 years.…”

Section: Related Workmentioning

confidence: 99%

OQ‐IICA: Optimal QoS‐aware intra‐inter cluster data aggregation technique for IoT‐assisted WSNs using hybrid optimization techniques

Satyavathi¹,

Sudhir

2023

Concurrency and Computation

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SummaryThe wireless sensor network (WSN) contains sensor nodes for understanding, communicating, and storing battery capacity data. Data collection can be defined as the process that base stations use to eliminate unwanted transmissions and provide mixed information. This improves energy efficiency and extends the life of low‐energy WSNs enabled by IoT (IoT‐WSNs). In this article, we propose an optimal QoS‐aware intra‐inter cluster data aggregation technique for WSNs using hybrid optimization techniques (OQ‐IICA). First, we introduce a modified bowerbird optimization (MBO) algorithm for balanced clustering which improves energy efficiency. Second, we develop a multi‐objective seagull optimization‐based decision‐making (MSO‐DM) algorithm to estimate the CH of clusters in the network. Next, we introduce a teacher‐inspired cappuccino search algorithm to ensure the quality of data transfer between nodes by learning through internal and cluster routing. Finally, the proposed OQ‐IICA algorithm compares the latest technologies in ICA, Leach, and Leach‐C power consumption, latency, throughput, latency, number of live nodes, routing, and grid length.

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“…The S-MAC protocol divides the clock into frames. The frame length is determined by the application [13]. The frame includes the working process and the sleep phase.…”

Section: Related Workmentioning

confidence: 99%

Information transmission simulation of Internet of things communication nodes under collision free probability equation

Chen

Al-Shalabi

2022

Applied Mathematics and Nonlinear Sciences

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Based on the background of the Internet of Things, this paper proposes a communication node information transmission protocol for wireless network sensors. This method adopts the strategy of alternating listening and sleeping. It can also reflect the overall characteristics of the monitoring range while meeting the real-time requirements. The protocol method proposed in this paper has the characteristics of low energy consumption and no synchronization. The algorithm reserves multi-hop timeslots at one time in the data forwarding direction at the frontier of data transmission. It avoids the delay caused by intermittent transmission of single-packet data on the forwarding path. The simulation results show that the energy efficiency and delay performance are much better than SMAC.

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Malicious Node Detection in Wireless Sensor Networks Using an Efficient Secure Data Aggregation Protocol

Cited by 24 publications

References 14 publications

An Iterative Convolutional Neural Network Based Malicious Node Detection (ICNN-MND) Protocol For Internet of Things

An Iterative Convolutional Neural Network Based Malicious Node Detection (ICNN-MND) Protocol For Internet of Things

OQ‐IICA: Optimal QoS‐aware intra‐inter cluster data aggregation technique for IoT‐assisted WSNs using hybrid optimization techniques

Information transmission simulation of Internet of things communication nodes under collision free probability equation

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