ESET uncovers AI-powered PromptLock ransomware using OpenAI gpt-oss:20b model, complicating detection with variable Lua ...

In the face of the rapidly evolving malware landscape, traditional detection methods encounter a formidable challenge due to critical vulnerabilities arising from biased training datasets skewed ...

Currently, the traffic speed prediction model based on deep learning has become a research hotspot in the field of transportation. With the rapid development of deep learning and the improvement of ...

Microsoft is announcing Project Ire today, an autonomous AI agent that can analyze and classify malware without assistance. Developed by Microsoft Research, Microsoft Defender Research, and ...

Although deep learning shows potential for early detection of STIs, there are challenges to ensuring the generalisability of such algorithms due to limited heterogeneous data. Standardised, diverse ...

🛡️ Malware Detection Using Machine Learning 📌 Project Overview This project implements a graph‑based machine learning framework to detect malware in Windows Portable Executable (PE) files.

Although Project Ire is a prototype, Microsoft says the 'AI agent' can (in some cases) reverse engineer any type of software on its own to determine if it's malicious.

However, such approaches are time consuming as they require extensive feature engineering, feature learning, and feature representation. By using the advanced MLAs such as deep learning, the feature ...