Ransomware Detection using Deep Learning

Download the malware and normal dataset using

cd downloads
python wgetall.py

unzip all files inside "./downloads/malware_data" directory with password 'infected'

cd ./downloads/malware_data
unzip -P infected \*.zip

Now, we can remove all of the unnecessary files, except for pcap files, inside "./downloads/malware_data" directory

cd ./downloads/malware_data
find . -not -name '*.pcap' -delete

Move all of the malware pcap files into directory "./malware_pcap/train_source/"

and all of the normal pcap files into directory "./normal_pcap/train/"

Now, to parse http header from pcap files, run:

./extract_http.sh

If you want to parse tcp header instead of http, run this instead:

./extract_tcp.sh

Use PCA to reduce dimensions of initial payloads.

python ./visual/pca.py ./dataset/train

It will produced a pickle file

Finally to run the deep neural network model

python simple_dnn.py

sdevkota007/RansomwareDetection