ABSTRACT: The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior using deep learning methods and ensuring interpretability of ...

This repository contains the source code, scripts, and supplementary materials for the paper: "A New Hybrid Model for Improving Outlier Detection Using Combined Autoencoder and Variational Autoencoder ...

Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...

Deep learning has emerged as a transformative tool for the automated detection and classification of seizure events from intracranial EEG (iEEG) recordings. In this review, we synthesize recent ...

Abstract: Malware continues to pose a serious threat to cybersecurity, especially with the rise of unknown or zero day attacks that bypass the traditional antivirus tools. This study proposes a hybrid ...

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...

Introduction: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in communication, social interactions, and repetitive behaviors. The heterogeneity of ...

The goal of this presentation is to inform people that using a 'pass only known good' methodology through a quantum approach simplifies the solution, and the future of information security will ...