Shilling attacks and detection methods

Usage

This repository houses the code to generate and detect attack profiles using generate_attack_files.py,supervised_detection_methods[baseline].py,ud_hmm.py

Shilling attacks

For generating attack profiles please refer to generate_attack_files.py

• Random Attack
• Average Attack
• Bandwagon Attack

Drive Link to load(already generated) attack profiles: https://drive.google.com/drive/folders/1jadqCCuKOLe6JTqSlvvyhq6EsgX5IN21?usp=sharing

Detection of shilling attacks

Supervised Approaches

The implementations for the following can be referred using supervised_detection_methods[baseline].py

• SVM
• kNN
• MLP
• Random Forest
• Naive Bayes (Gaussian)

Unsupervised Approaches

The implementations for the following can be referred using ud_hmm.py

• UD-HMM