Thavavel Vaiyapuri

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.

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.

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.

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.

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.