In his paper “Malware Detection Using Machine Learning” Dragos Gavrilut aimed for developing a detection system based on several modified perceptron algorithms. For different algorithms, he achieved ...

This model can be used to detect malware families and predict whether a review, whether positive or negative, is malware. It can also be used to train other machine learning techniques. This work ...

The current challenge, in the cyber world is to identify and categorize software. To tackle this machine learning can be utilized to detect and classify malware by analyzing patterns, behaviors and ...

The machine learning-based method for now is all about detection. It's up to the security analyst or other tools to decide what to do next with the newly discovered malicious code, he says.

In an effort to bypass security software using AI and machine learning to detect malware, cybercriminals have begun to add text from news articles about the coronavirus to the TrickBot and Emotet ...

Using unsupervised machine learning techniques, security experts can cluster URLs or domains to identify DGAs (domain generation algorithms), used by malware creators to generate domains that act as ...

New types of malware that can detect when installed on a virtual machine are going into hibernation, making them hard to track down. Skip to main content Menu ...

In 2024 alone, fileless malware like HeadCrab doubled its grip on cloud servers, silently mining cryptocurrency from over 2,300 victims. Meanwhile, a 1,400% surge in these invisible attacks ...