Ons Aouedi's repositories
clustered-federated-learning
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
Attack-and-Anomaly-Detection-in-IoT-Sensors-in-IoT-Sites-Using-Machine-Learning-Approaches
Attack and Anomaly detection in the Internet of Things (IoT) infrastructure is a rising concern in the domain of IoT. With the increased use of IoT infrastructure in every domain, threats and attacks in these infrastructures are also growing commensurately. Denial of Service, Data Type Probing, Malicious Control, Malicious Operation, Scan, Spying and Wrong Setup are such attacks and anomalies which can cause an IoT system failure. In this paper, performances of several machine learning models have been compared to predict attacks and anomalies on the IoT systems accurately. The machine learning (ML) algorithms that have been used here are Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). The evaluation metrics used in the comparison of performance are accuracy, precision, recall, f1 score, and area under the Receiver Operating Characteristic Curve. The system obtained 99.4% test accuracy for Decision Tree, Random Forest, and ANN. Though these techniques have the same accuracy, other metrics prove that Random Forest performs comparatively better.
cellular-traffic-analysis
Analysis of real cellular traffic captured on a device
cnn-lstm-bilstm-deepcnn-clstm-in-pytorch
In PyTorch Learing Neural Networks Likes CNN(Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) 、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM
CollaborativeFairFederatedLearning
Official implementation of our work "Collaborative Fairness in Federated Learning."
Security-and-Robustness-of-Deep-Learning-in-Wireless-Communication-Systems
A research oriented repository on the Security and Robustness of Deep Learning for Wireless Communication Systems
ConvLSTM_pytorch
Implementation of Convolutional LSTM in PyTorch.
DeepConvLSTM
Deep learning framework for wearable activity recognition based on convolutional and LSTM recurretn layers
federated-learning-1
Everything about Federated Learning (papers, tutorials, etc.) -- 联邦学习
GMAN
GMAN
non-iid-dataset-for-personalized-federated-learning
Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective".
Python-TheNoTheoryGuide
Jupyter NoteBooks to get you boosted with the basics of python with hands-on-practice.
sherpa
Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
STCNet
Source code of IEEE JSAC
tensorflow-without-a-phd
A crash course in six episodes for software developers who want to become machine learning practitioners.
traffic_prediction
The source code for citywide wireless traffic prediction based on deep learning (DenseNet)