Explore live open-source projects and AI models.

Public datasets of malware and benign executable files (Windows EXE files). The dataset can be used by cybersecurity researchers focusing on the area of malware detection. It is suitable for training and testing both machine learning and deep learning algorithms.

Malware detection demo using machine learning.

Leveraging the power of Machine Learning as a tool, we delve into the realm of app permissions to discern the true nature of applications, whether they harbor malicious or benign intent. By analyzing and predicting based on these permissions, we unlock valuable insights to safeguard users in the ... Read more

Open source malware detection program using machine learning algorithms on system call traces.

Use machine learning to classify malware. Malware analysis 101. Set up a cybersecurity lab environment. Learn how to tackle data class imbalance. Unsupervised anomaly detection. End-to-end deep neural networks for malware classification. Create a machine learning Intrusion Detection System (IDS).... Read more

File integrity monitor with malware detection using machine learning

AI-powered Cybersecurity Threat Detection System using Machine Learning and Security Logs. Detects malware, phishing attacks, and network intrusions using Python, TensorFlow, and SIEM logs.

A comprehensive malware detection and dynamic analysis system, designed to analyse malware samples and benign files & classify them using a pre-trained machine learning model, and perform dynamic analysis on the detected malware.

This project analyzes PE information of exe files to detect malware. In this repository you will learn how to create your own dataset and will be able to see the use of machine learning models using the dataset. We will use machine learning for detect malware.

Advanced detection of port scanning, DoS and malware attacks using Machine Learning techniques