Popular Malware-Samples for research and educational purposes.(60+ Samples!)
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Updated
Mar 14, 2022
Popular Malware-Samples for research and educational purposes.(60+ Samples!)
Detecting malicious URLs using an autoencoder neural network
Malware Classification using Machine learning
A large-scale database of malicious software images
Training Vision Transformers from Scratch for Malware Classification
Malware Detection using Machine Learning (MDML)
Malware Classification and Labelling using Deep Neural Networks
android-malware-classification using machine learning algorithms
This GitHub repository contains an implementation of a malware classification/detection system using Convolutional Neural Networks (CNNs).
PyTorch dataset loader for image, text, malware, and medical classification datasets
Few-Shot malware classification using fused features of static analysis and dynamic analysis (基于静态+动态分析的混合特征的小样本恶意代码分类框架)
Official implementation for the paper "On deceiving malware classification with section injection"
Malware detector and classifier based on static analysis of PE executables
Source code of Malware Classification by Learning Semantic and Structural Features of Control Flow Graphs (TrustCom 2021)
A malware image dataset based on dynamic analysis and a classification model based on capsule network.
Malware Classification using the dataset provided by Microsoft
Malware Byteplot Image Classification using Machine Learning and Deep Learning
FewShot Malware Classification based on API call sequences, also as code repo for "A Novel Few-Shot Malware Classification Approach for Unknown Family Recognition with Multi-Prototype Modeling" paper.
in this project we used image processing Technique to classify 9 class malwares our final goal is to reach an appropriate model with high accuracy and small size and computational cost
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