SEPTun

Performance Tuning Guide

A guide to tuning Suricata for maximum performance in network intrusion detection systems

Suricata Extreme Performance Tuning guide

GitHub

204 stars
22 watching
22 forks
Language: Makefile
last commit: over 8 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

RepositoryDescriptionStars
pevma/septun-mark-iiA tuning guide for optimizing the performance of a network intrusion prevention system114
pevma/massdeploysuricataAutomates the deployment and updating of Suricata network intrusion detection system software.9
kirthevasank/nasbotAn implementation of Neural Architecture Search with Bayesian Optimization and Optimal Transport133
baai-dcai/visual-instruction-tuningA dataset and model designed to scale visual instruction tuning using language-only GPT-4 models.164
jmrichardson/tunetaAutomates optimization of technical indicators for machine learning models in finance421
assafmo/couchdb-linux-performanceLinux tuning guide for optimizing CouchDB performance37
icoz69/stablellavaA tool for generating and evaluating multimodal Large Language Models with visual instruction tuning capabilities93
sahilshekhawat/optimizing-linux-performance-a-hands-on-guide-to-linux-performance-toolsA comprehensive guide to improving Linux performance using various tools and techniques68
travisbgreen/hunting-rulesProvides Suricata IDS alert rules for detecting network anomalies154
zygmuntz/hyperbandA hyperparameter tuning framework with support for multiple machine learning models and algorithms.594
sebdraven/iocmiteAutomates importing threat intelligence data into Suricata's surveillance system37
nicholas-leonard/drmadA toolbox for efficient hyperparameter tuning in deep learning using Bayesian optimization and automatic differentiation23
neo23x0/yara-performance-guidelinesA guide providing performance optimization tips for YARA rules126
tobegit3hub/advisorAn open-source hyperparameters tuning system for black box optimization1,550
microsoft/archaiAutomates the search for optimal neural network configurations in deep learning applications468