Android malware using artificial intelligence has been discovered carrying out hidden ad fraud on infected devices. It automatically clicks ads through concealed browser windows and spreads mainly ...

In 2023, Ethan Mollick and Lilach Mollick published a paper titled Assigning AI: Seven Approaches for Students, with Prompts. At the time, generative AI tools were far less capable than what we now ...

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...

Threat actors are testing malware that incorporates large language models (LLMs) to create malware that can evade detection by security tools. In an analysis published earlier this month, Google's ...

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 ...

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...

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 ...

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 ...