WADAC

WADAC is a privacy-preserving anomaly detection and attack classification framework developed by ReSILIoT. This repository comprises of the source code and sample datasets for work done in the paper WADAC: Privacy-Preserving Anomaly Detection and Attack Classification on Wireless Traffic (https://dl.acm.org/citation.cfm?id=3212480.3212495)

Prerequisites

• The Feature Extractor module of WADAC is developed in python 2.7.0
• Feature Selection, Anomaly Detector and Attack Classification are developed in R (3.4.2)

Test Run

• Run unzip_all.R to unzip large files in the repository
• To test and visualize WADAC, refer to Readme.md in ./demo_code
• To extract features used in the paper, run extract_features.py from feature_extraction folder
• To replicate results of paper, for feature selection, anomaly detection and attack classification, run main.R in Anomaly_detector folder

Authors

• Ragav Sridharan
• Rajib Ranjan Maiti
• Nils Ole Tippenhauer

License

This project is licensed under the MIT License - see the LICENSE.md file for details