PCMag

Malware Is Sleeping on the Blockchain, and It's Already Infected Dozens of Global Targets

Experts warn the campaign could outpace past global cyberattacks, with hundreds of thousands of credentials already ...

GitHub adds AI-powered bug detection to expand security coverage

GitHub is adopting AI-based scanning for its Code Security tool to expand vulnerability detections beyond the CodeQL static ...
Bleeping Computer

New Android malware uses AI to click on hidden browser ads

A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact with specific advertisement elements. The mechanism relies on visual ...
Infosecurity-magazine.com

Malware Manipulates AI Detection in Latest npm Package Breach

A new attempt to influence AI-driven security scanners has been identified in a malicious npm package. The package, eslint-plugin-unicorn-ts-2 version 1.2.1, appeared to be a TypeScript variant of the ...
Scientific Research Publishing

An, J. and Cho, S. (2015) Variational Autoencoder Based Anomaly Detection Using Reconstruction Probability. Special Lecture on IE, 2, 1-18.

ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...
Scientific Research Publishing

Ferrag, M.A., Maglaras, L., Moschoyiannis, S. and Janicke, H. (2020) Deep Learning for Cyber Security Intrusion Detection: Approaches, Datasets, and Comparative Study. Journal ...

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 ...
Futurism

Malware Is Now Using AI to Rewrite Its Own Code to Avoid Detection

Add Futurism (opens in a new tab) Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Researchers at Google’s ...
IEEE

Zero-Day Malware Detection Using Autoencoder and Hybrid Deep Learning Model

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 ...