amin-tayebi / Attack-Detection-in-IoT-Network-Traffic-with-Neural-network-Deep-Learning-model

IoT Attack Detection with Deep Learning Analysis (2019)

Attack Detection in IoT Network Teraffic with Neural network Deep Learning model (2019)

we created a large integrated dataset of IoT traffic flows, coming from four different network scenarios, in order to have a benchmark for future research. Then we used this dataset to test the effectiveness of our deep learning network model, made of different hidden layers, and we compare its outcomes with the ones obtained through traditional machine learning approaches, demonstrating the superiority of our deep learning architecture in both a binary and multinomial classification. Our neural network architecture has been implemented using the Python programming language, in particular Tensorflow 2.1.09, an open source software library for high-performance numerical computation, and Keras 2.3.110, a Python-based high-level neural networks API. IEEE paper: https://ieeexplore.ieee.org/iel7/9200848/9206590/09207171.pdf

Special Thanks

A special thanks goes to Prof Luca Veltri(https://github.com/thingsstack) and Prof Riccardo Pecori(https://sites.google.com/site/riccardopecoriphd/) for supporting and guidance.