Projects 

 1.Fusion of Feature Selection Techniques and Machine learning Algorithms for Attack Classification on 802.11 Wi-Fi AWID Dataset

 Using Aegean Wi-Fi intrusion dataset (AWID) , a model is designed for detection and classification of network intrusions using Machine Learning Algorithms. The classes of attacks were impersonation, flooding, and injection.

2.Analyzing Deep learning and Machine learning Models along with feature selection for Attack Classification on 802.11 Wi-Fi AWID Dataset

A Classification comparative model is designed based on deep learning techniques including multi-layer perceptrons (MLP), long-short-term memory (LSTM), and autoencoders for binary and multi-class classification using Aegean Wi-Fi intrusion dataset (AWID).

3. Anomaly Detection in Aegean Wi-Fi intrusion dataset (AWID)

 Using Aegean Wi-Fi intrusion dataset (AWID) several models are constructed by upsclaing and downscaling the parameters fed into the model to check the performance of the model each time and detect anomaly .