Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior performance compared to conventional non-machine learning approaches when ...

Machine learning helps improve accuracy and efficiency of small-molecule calculations Microsoft researchers used deep learning to create new DFT model by Sam Lemonick, special to C&EN June 20, 2025 ...

The increasing reliance on compressed file formats for data storage and transmission has made them attractive vectors for malware propagation, as their structural complexity enables evasion of ...

Kara, I., Ok, M. and Ozaday, A. (2022) Characteristics of Understanding URLs and Domain Names Features The Detection of Phishing Websites with Machine Learning Methods. IEEE Access, 10, 124420-124428.

Malware with corrupted DOS and PE headers evades detection for weeks, decrypts TLS-based C2 and enables full attacker control.

Microsoft’s Digital Crimes Unit filed a legal action against Lumma Stealer last week, after it found nearly 400,000 Windows computers globally infected by the information-stealing malware in … ...

Over the past year, Microsoft Threat Intelligence observed the persistent growth and operational sophistication of Lumma Stealer, an info-stealing malware used by multiple financially motivated threat ...

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

Since the start of the year, the Russian state-backed ColdRiver hacking group has been using new LostKeys malware to steal files in espionage attacks targeting Western governments, journalists ...

Malware identification is essential for safeguarding digital systems from cyber attacks, and machine learning techniques are proving to be efficient in this field. This systematic literature re-view ...