Abstract: Anomaly detection in environmental datasets is critical for identifying unusual patterns that could signal potential hazards or changes in environmental conditions. Traditional methods often ...

Security Operation Centers (SOC) continuously monitor system logs to detect suspicious activities such as brute-force attacks, unauthorized access, or privilege abuse. However, the large volume and ...

Abstract: The rapid expansion of data from diverse sources has made anomaly detection (AD) increasingly essential for identifying unexpected observations that may signal system failures, security ...

Introduction: In swine disease surveillance, obtaining labeled data for supervised learning models can be challenging because many farms lack standardized diagnostic routines and consistent health ...

Melanoma remains one of the hardest skin cancers to diagnose because it often mimics harmless moles or lesions. While most artificial intelligence (AI) tools rely on dermoscopic images alone, they ...

ABSTRACT: The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based ...

Why is this important? This upgrade will allow users to pull source material directly from their Gmail, Drive, or Chat, eliminating the need to manually download and upload files. Why should I care?

ABSTRACT: Healthcare cyberattacks rise as attackers leverage system and human vulnerabilities. The existing security systems are technology-driven as they focus on system resilience, but they neglect ...

This repository contains an end-to-end MLOps project that builds, tests, and containerizes a real-time anomaly detection API using time-series data. The Numenta Anomaly Benchmark (NAB) dataset is used ...