GitHub

RNN-DAS: A New Deep Learning Approach for Detection and Real-Time Monitoring of Volcano-Tectonic Events Using Distributed Acoustic Sensing

RNN-DAS is an innovative Deep Learning model based on Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells, developed for real-time Volcano-seismic Signal Recognition (VSR) using ...
IEEE

FSL-IDS: Federated Semi-Supervised Learning Intrusion Detection System for In-Vehicle Networks

Abstract: Intelligent in-vehicle networks (IVNs) are increasingly exposed to complex security threats. Traditional supervised deep learning methods depend heavily on extensive labeled datasets, ...

Rohith Vegensa: Cybersecurity In Fueling Systems-Protecting Transactions And Preventing Fraud

Rohith Vegesna is a software engineer specializing in secure, cloud-connected fueling systems, with a strong focus on IoT, real-time monitoring, and cybersecurity.
Devdiscourse

AI moves to the core of cyber defense as attacks grow more complex

Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...
IEEE

IDTM: Interpretable Intrusion Detection with Tsetlin Machine: A Binarization-Guided Approach

Abstract: The increasing sophistication of cyberattacks demands an intelligent and interpretable intrusion detection system (IDS) capable of operating efficiently in real-time environments. In this ...

iOT365 Introduces LLM-Native Autonomous SOC for Industrial Environments

Autonomous, LLM-native SOC unifying IDS, SIEM, and SOC to eliminate Tier 1 and Tier 2 operations in OT and critical ...