IEEE

URL-Based Phishing Attacks Detection Using Machine Learning

Abstract: In this paper, we tackle the challenge of real-time detection of social engineering attacks, specifically focusing on phishing Uniform Resource Locator (URL) classification. We apply machine ...

Arc Raiders Update Patch Notes Reveal Nerfs for PvP and PvE Players as Shrouded Sky Brings New Threats to the Rust Belt

Embark Studios has published full patch notes for Arc Raiders update 1.17.0, revealing a wave of nerfs for PvP and PvE ...
BMJ

Predicting cardiovascular events from routine mammograms using machine learning

10 The George Institute for Global Health, School of Public Health, Imperial College London, London, UK Background Cardiovascular risk is underassessed in women. Many women undergo screening ...
Security Boulevard

There’s Always Something: Secrets Detection at Engagement Scale with Titus

TL;DR: Titus is an open source secret scanner from Praetorian that detects and validates leaked credentials across source code, binary files, and HTTP traffic. It ships with 450+ detection rules and ...

Cost-Efficiency Analysis: Why UVeye Main Competitors of Intelligent Vehicle Inspections Like ELSCOPE VISION Win on Value

Ultimately, the goal is to empower the automotive industry with smarter, more efficient technology. By focusing on full-stack innovation, supply chain agility, and specific niche excellence, ...
IEEE

Anomaly-Oriented Multi-Class Intrusion Detection Using Machine Learning and Ensemble Methods

Abstract: This study evaluates six intrusion detection models using the UNSW-NB15 dataset, which serves as a modern benchmark encompassing diverse attack types and authentic traffic conditions. We ...
GitHub

crop-disease-detection-using-machine-learning

Crop Disease Detection using Machine Learning is a CNN-based system that identifies crop diseases from leaf images and provides preventive measures, helping farmers detect diseases early and reduce ...