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android-malware-detection-1's Introduction

Android-Malware-Detection

Android Malware Detection using Deep Learning

  • Classification of android apps done based on pseudo-dynamic analysis of system API Call sequences.
  • Developed a Deep Convolutional Neural network (CNN) and a Recurrent Neural Network (LSTM) model.
  • Compared performance of these Deep Neural Network models with Naive Bayes Classifier.

Files

File Description
generate_dict.py Generates global dictionary for storing mapping all distinct API Calls to numbers in the dataset and pickles the dictionary
load_dict.py Loads the dictionary of API Calls
extract_all_features.py Extracts all feature vectors (of size n X m X h) for 8 testcases in dataset and pickles them
extract_all_features_compressed.py Extracts all feature vectors (of size n X h) for 600 apps in dataset and pickles them
data_reader.py Loads all pickled feature vectors
uncompress.py Uncompresses features to one-hot form
cnn2.py and cnn3.py Different cnn architectures
lstm.py lstm model
nb.py Naive bayes model

android-malware-detection-1's People

Contributors

vikram-mm avatar

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