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Thavavel Vaiyapuri

Researcher at Salman bin Abdulaziz University

Publications -  35
Citations -  440

Thavavel Vaiyapuri is an academic researcher from Salman bin Abdulaziz University. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 4, co-authored 21 publications receiving 78 citations.

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Journal ArticleDOI

Identifying and Benchmarking Key Features for Cyber Intrusion Detection: An Ensemble Approach

TL;DR: The obtained results prove that the proposed approach contributes more potential features compared to the state-of-the-art approaches, leading to achieve a promising performance gain in the detection rate, the false alarm rate, and the detection time.
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Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM

TL;DR: An extensive set of experiments demonstrates the generalization ability of the proposed model for unseen attacks and confirms it as a competitive approach over the recent state-of-the-art intrusion detection baselines, emphasizing that the proposed approach has potential to serve as a baseline for building an effective IDS.
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A Novel Hybrid Optimization for Cluster‐Based Routing Protocol in Information-Centric Wireless Sensor Networks for IoT Based Mobile Edge Computing

TL;DR: An IoT enabled cluster based routing (CBR) protocol for information centric wireless sensor networks (ICWSN), named CBR- ICWSN is proposed, which has outperformed the compared methods interms of network lifetime and energy efficiency.
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An automated deep learning based anomaly detection in pedestrian walkways for vulnerable road users safety

TL;DR: An automated deep learning based anomaly detection technique in pedestrian walkways (DLADT-PW) for vulnerable road user's safety is developed and the obtained experimental values confirmed the superior characteristics of the DLADT -PW technique by achieving a maximum detection accuracy.
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Blockchain-assisted secure image transmission and diagnosis model on Internet of Medical Things Environment

TL;DR: Deep learning with blockchain-assisted secure image transmission and diagnosis model for the IoMT environment, which comprises a few processes namely data collection, secure transaction, hash value encryption, and data classification.