Code & Development · GitHub ·171 ★

Intrusion-and-anomaly-detection-with-machine-learning

Machine learning algorithms applied on log analysis to detect intrusions and suspicious activities.

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Details

Author
slrbl
Category
Code & Development
Platform
GitHub
Framework
custom
Language
python
Stars
171
First indexed
2026-05-15
Last active
2025-11-06
Directory sync
2026-05-15
@slrbl

Overview

Machine learning algorithms applied on log analysis to detect intrusions and suspicious activities.

Quick start

git

git clone https://github.com/slrbl/Intrusion-and-anomaly-detection-with-machine-learning

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What Intrusion-and-anomaly-detection-with-machine-learning can do

llmsecurityanaly
  • Llm — llm task automation.
  • Security — Scans systems and reviews code for vulnerabilities.
  • Analy — analy task automation.

Frequently asked questions

What is Intrusion-and-anomaly-detection-with-machine-learning?
Machine learning algorithms applied on log analysis to detect intrusions and suspicious activities.
How do I install Intrusion-and-anomaly-detection-with-machine-learning?
Use git: `git clone https://github.com/slrbl/Intrusion-and-anomaly-detection-with-machine-learning`. Full setup details on the source page linked above.
Is Intrusion-and-anomaly-detection-with-machine-learning open source?
Intrusion-and-anomaly-detection-with-machine-learning is published on GitHub.
What are alternatives to Intrusion-and-anomaly-detection-with-machine-learning?
Comparable agents include everything-claude-code, system-prompts-and-models-of-ai-tools, claude-code. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for Intrusion-and-anomaly-detection-with-machine-learning is sourced from GitHub, published by slrbl.

Last scraped: · First indexed:

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