GNOM - Graph Neural Network Security by RESK

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    │   Graph Neural Network Monitoring      │
    │           by RESK Security             │
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When Traditional Security meets Graph Neural Networks

GNOM is an advanced security solution powered by Graph Neural Networks (GNN) developed by RESK Security. It transforms your network infrastructure into a dynamic graph structure for real-time threat detection and vulnerability assessment.

Key Features

Core Features

→ Real-time network topology mapping to GNN structures
→ Advanced node feature extraction and edge relationship analysis
→ Reinforcement Learning-based attack prediction
→ Vulnerability assessment through graph analysis

╔═══════════════════════════════════════╗ ║ Enterprise Network ║ ║ ┌──────┐ ┌──────┐ ┌──────┐ ║ ║ │Server ├────┤Switch├────┤ PC │ ║ ║ └──────┘ └──────┘ └──────┘ ║ ║ │ │ │ ║ ║ ┌──────┐ ┌──────┐ ┌──────┐ ║ ║ │Firewall │Router│ │Printer│ ║ ║ └──────┘ └──────┘ └──────┘ ║ ╚═══════════════════════════════════════╝ │ ▼ ╔═══════════════════════════════════════╗ ║ Conversion to GNN structure ║ ║ [Node]───(Edge)───[Node]───(Edge) ║ ║ │ │ ║ ║ │ │ ║ ║ (Edge) (Edge) ║ ║ │ │ ║ ║ [Node]───(Edge)───[Node] ║ ╚═══════════════════════════════════════╝ │ ▼ ╔═══════════════════════════════════════╗ ║ GNN Model ║ ║ ┌─────────────────────┐ ║ ║ │ GNN Conv. Layers │ ║ ║ │ [A] → [H] → [Z] │ ║ ║ └─────────────────────┘ ║ ║ ┌─────────────────────┐ ║ ║ │ Node Aggregation │ ║ ║ └─────────────────────┘ ║ ╚═══════════════════════════════════════╝ │ ▼ ╔═══════════════════════════════════════╗ ║ RL Agent ║ ║ ┌─────────────────────────┐ ║ ║ │ State │ Action │ Reward │ ║ ║ └─────────────────────────┘ ║ ║ │ Policy π(s|a) │ ║ ║ │ Value V(s) │ ║ ║ └─────────────────────────┘ ║ ╚═══════════════════════════════════════╝ │ ▼ ╔═══════════════════════════════════════╗ ║ Attack Simulation ║ ║ DDoS Malware Phishing ║ ║ │ │ │ ║ ║ ▼ ▼ ▼ ║ ║ ┌───────────────────────────┐ ║ ║ │ Vulnerability Assessment │ ║ ║ └───────────────────────────┘ ║ ╚═══════════════════════════════════════╝ │ ▼ ╔═══════════════════════════════════════╗ ║ Vulnerability Prediction ║ ║ Risk: Low Medium High ║ ║ [_] [_] [X] ║ ║ ┌───────────────────────────┐ ║ ║ │ Ranking of Risky Nodes │ ║ ║ └───────────────────────────┘ ║ ╚═══════════════════════════════════════╝ │ ▼ ╔═══════════════════════════════════════╗ ║ Security Recommendations ║ ║ 1. Firmware updates ║ ║ 2. Firewall strengthening ║ ║ 3. Employee training ║ ║ 4. Network segmentation ║ ║ 5. Continuous monitoring ║ ╚═══════════════════════════════════════╝

Graph Construction

GNOM converts your network infrastructure into a mathematical graph representation where:

◉ Nodes represent network devices
◉ Edges represent connections and data flows
◉ Node features capture device characteristics
◉ Edge features represent connection properties

GNN Architecture

Our solution employs:

◉ Multiple GNN convolutional layers for deep feature extraction
◉ Advanced node aggregation techniques
◉ Message passing neural networks for information propagation
◉ Attention mechanisms for focusing on critical network segments

When Traditional Security meets Graph Neural Networks

Key Features

Core Features

Graph Construction

GNN Architecture

Documentation

Technical Overview

Implementation Guide

When Traditional Security meets Graph Neural Networks

Key Features

Core Features

Graph Construction

GNN Architecture

Documentation

Technical Overview

Implementation Guide

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