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A Python toolkit for rule-based/unsupervised anomaly detection in time series
Advanced Deep Learning with Keras, published by Packt
A curated list of Best Artificial Intelligence Resources
This is a paper list about Machine Learning for IDSes
Classification anomaly detection in IOT with Machine Learning
UNSW-NB15 Dataset
This project is part of my capstone project at The University of Sydney
Research of mechanisms for detecting network anomalies using machine learning
This repo contains the files created during the Multi Skill Training program conducted @ Vignan's Institute of Engineering for Women
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.
Audio super resolution using neural networks
Repository of Bachelor's Major Project on Botnet Detection
Predicting botnet attack for IOT devices using Machine learning
NetFlow based botnet detection using supervised learning
Building a chatbot with bidirectional LSTM and attention mechanism with tensorflow and keras
CSE-CIC-IDS-2018 analyze with Random Forest
CICIDS2017 dataset
Experiments with CICIDS2017 data set from UNB
The purpose of this repository is to demonstrate the steps of processing CICIDS2017 dataset using machine learning algorithms.
Handling imbalanced data to predict if customers will subscribe to a term deposit. Determine significant contributing features. Customer Segmentation to identify key customer groups to target the product to.
This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets
Undergraduate section of CMPT 419/726 Machine Learning: Theoretical justification for and practical application of, machine learning algorithms
DISEÑO Y EVALUACIÓN DE REDES NEURONALES CONVOLUCIONALES PARA UN SISTEMA DE DETECCIÓN DE INTRUSIONES
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
Machine Learning for Anomaly Detection (Network Intrusion Detection) & Cyber Security Utilities
Cyber Attack Detection thanks to Machine Learning Algorithms
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.