An Efficient Control Strategy for an Extended Switched Coupled Inductor Quasi-Z-Source Inverter for 3Φ Grid Connected System

Meenalochini, P; Karthick, R.; Sakthivel, E.

doi:10.1142/s0218126624500117

Cited by 29 publications

(1 citation statement)

References 39 publications

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“…As a result, they are attacked and hacked by botnets that can be employed for initiating distributed denial-of-service (DDoS) against associations (Karthick, Senthilselvi, et al, 2023;Khan et al, 2021;Wang et al, 2022). Network intrusion detection systems (NIDSs) can be executed in IoT networks to preserve three security principles of information systems; they are availability, confidentiality, and integrity (Meenalochini et al, 2023;Rahman et al, 2021;Shajin et al, 2022). It analyzes and scans network traffic to find patterns and signs that denote an effective assault.…”

Section: Introductionmentioning

confidence: 99%

Intrusion detection system using metaheuristic fireworks optimization based feature selection with deep learning on Internet of Things environment

Jayasankar,

Kiruba Buri,

Maheswaravenkatesh

2023

Journal of Forecasting

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Internet of Things (IoT), cloud computing, and other significant advancements in communication have created new security challenges. Due to these advancements and the ineffectiveness of the current security measures, cyber‐attacks are also increasing quickly. Recently, several artificial intelligence (AI)–based solutions have been presented for various secure applications, such as intrusion detection. This article proposes an intrusion detection system using dynamic search fireworks optimization–based feature selection with optimal deep recurrent neural network (DFWAFS‐ODRNN) model in IoT environment. The presented DFWAFS‐ODRNN model follows a two‐stage process, namely, feature selection and intrusion classification. In the first phase, the DFWAFS‐ODRNN model elects an optimal subset of features using the dynamic search fireworks optimization algorithm (DFWAFS) technique. Next, in the second stage, the intrusions are identified and categorized using the DRNN model. At last, the hyperparameters of the DRNN are optimally chosen by the Nadam optimizer. A detailed simulation analysis of the DFWAFS‐ODRNN model is validated on benchmark intrusion detection system (IDS) dataset, and the outcomes show the efficacy of intrusion detection. The proposed model efficiently detects the intrusion detection with an accuracy of 96.11%.

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Section: Introductionmentioning

confidence: 99%

Intrusion detection system using metaheuristic fireworks optimization based feature selection with deep learning on Internet of Things environment

Jayasankar,

Kiruba Buri,

Maheswaravenkatesh

2023

Journal of Forecasting

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Energy efficient data dissemination in wireless sensor network enabled IoT using domain‐adaptive message passing graph neural network

Shiny,

Ram,

et al. 2024

Int J Communication

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SummaryIn the past few years, restricted wireless sensor networks (WSNs) enabled the Internet of Things (IoT) have attracted significant attention and expansion to enhance service delivery and resource efficiency. Dissemination is a service offered by WSN that uses radio transmission and over‐the‐air programming for updating the deployed sensor nodes through online. The centralized data dissemination methods are replaced by the distributed approaches because they affect the drawbacks of a single point of failure, no scalability, and insecurity. Therefore, an Energy Efficient Protocol for Data Dissemination in Wireless Sensor network‐enabled IoT using Domain‐Adaptive Message Passing Graph Neural Network (EEP‐WSN‐IoT‐DMPGNN) is proposed in this paper. The nodes are formed as clusters utilizing the Deep Fuzzy Curriculum Clustering (DFCC) technique that rewards nodes belonging to a given cluster. By using the Crayfish Optimization Algorithm (COA), the Cluster Head (CH) selection optimally chose the ideal CH and satisfies the multiple objective functions, such as energy, delay, traffic density, and distance. Afterward, domain‐adaptive Message Passing Graph Neural Network (DMPGNN) based routing protocol is developed, the input given to the routing protocol includes a sink, action history, future node, and maximum‐distance node, which attains enhanced data transfer in the chosen path. The proposed technique attains a lower no. of dead nodes, lower energy consumption, and higher Network Lifetime while analyzed with existing techniques, such as routing technique depending on deep learning for effectual data transmission in 5G WSN communication (DL‐RPDT‐WSN), Reinforcement‐Learning base energy effectual optimized routing protocol in WSN (RL‐EERP‐WSN), and Energy‐efficient intellectual routing method for IoT‐enabled WSN (EIR‐IoT‐WSN), respectively.

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An efficient cluster head selection in WSNs using transient search optimization (TSO) algorithm

Subramanian,

Muthusamy,

Kulandaivelu

et al. 2024

Int J Communication

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SummaryIn this manuscript, a nature‐inspired optimization method, named transient search optimization (TSO), is proposed. Energy‐based monetary custom is a serious issue on the wireless sensor network (WSN). Here, the network clustering is an effectual technique to reduce node energy depletion and increased network lifetime. The proposed method aims to improve the efficiency of sensor nodes (SNs) by reducing their detachment, minimizing energy transmission, and protecting excessive energy stored in the nodes. This approach helps decrease delays, reduce traffic flow, and optimize network performance. The execution is implemented on the NS2 software. The experimental outcomes exhibit that the proposed system performs better based on two wireless sensor architectures, such as 50 nodes and 100 nodes. The parameter produces 52.24%, 54.38%, and 56.37% better network lifetime; 44.71%, 46.24%, and 49.45% higher alive node; and 39.26%, 36.26%, and 28.65% lesser dead SNs compared with existing techniques like multi‐objective cluster head (CH)–based energy‐aware optimized routing approach in wireless sensor network (MOCH‐ORR‐WSN), energy effective CH selection with improved sparrow search algorithm in WSN (ECH‐ISS‐WSN), and energy effectual cluster basis routing protocol under butterfly optimization along ant colony optimization algorithms for WSN (EEC‐BOA‐ACO‐WSN).

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An Efficient Control Strategy for an Extended Switched Coupled Inductor Quasi-Z-Source Inverter for 3Φ Grid Connected System

Cited by 29 publications

References 39 publications

Intrusion detection system using metaheuristic fireworks optimization based feature selection with deep learning on Internet of Things environment

Intrusion detection system using metaheuristic fireworks optimization based feature selection with deep learning on Internet of Things environment

Energy efficient data dissemination in wireless sensor network enabled IoT using domain‐adaptive message passing graph neural network

An efficient cluster head selection in WSNs using transient search optimization (TSO) algorithm

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