32 Open source projects that are alternatives of or similar to ML-ATIC

NetFlow data source for Spark SQL and DataFrames

Manito Networks Flow Analyzer

[DEPRECATED] Graylog NetFlow plugin

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

Container traffic visibility library based on eBPF

Network flow analytics (Netflow, sFlow and IPFIX) with the Elastic Stack

数据可视化

Responsive NetFlow visualizer built on top of nfdump tools.

DynamiteNSM is a free Network Security Monitor developed by Dynamite Analytics to enable network visibility and advanced cyber threat detection

Open source components and extensions for nProbe

A set of tools and examples to run a flow-pipeline (sFlow, NetFlow)

softflowd: A flow-based network traffic analyser capable of Cisco NetFlow data export software.

PyPI "netflow" package. NetFlow v9 parser, collector and analyzer implemented in Python 3. Developed and tested with softflowd

Enterprise Network Flow Collector (IPFIX, sFlow, Netflow) from Verizon Media

Pcap editing and replay tools for *NIX and Windows - Users please download source from

pmacct is a small set of multi-purpose passive network monitoring tools [NetFlow IPFIX sFlow libpcap BGP BMP RPKI IGP Streaming Telemetry].

NFStream: a Flexible Network Data Analysis Framework.

The high-scalability sFlow/NetFlow/IPFIX collector used internally at Cloudflare.

Netflow processing tools

Web-based Traffic and Security Network Traffic Monitoring

Netflow iptables module for Linux kernel (official)

FastNetMon - very fast DDoS sensor with sFlow/Netflow/IPFIX/SPAN support

High performance sFlow/IPFIX/NetFlow Collector

Flow-Indexer indexes flows found in chunked log files from bro,nfdump,syslog, or pcap files

pastaʃ'ʃ = Spaghetti I/O Event Data Processing, Interpolation, Correlation and beyond 🍝

A collection of research papers on decision, classification and regression trees with implementations.

Decision Tree with PEP,MEP,EBP,CVP,REP,CCP,ECP pruning algorithms,all are implemented with Python(sklearn-decision-tree-prune included,All are finished).

An implementation of the paper "A Short Introduction to Boosting"

📈 Click-Through Rate Prediction using Logistic Regression and Tree Algorithms

Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

Solutions to kdd99 dataset with Decision tree and Neural network by scikit-learn

Feature coded UNSW_NB15 intrusion detection data.