Network Security Agent

Project Overview

A high-performance network security monitoring system that combines real-time traffic analysis with machine learning-based anomaly detection. The system is designed to process network traffic at scale while maintaining low latency and high throughput.

Technical Architecture

System Architecture

flowchart TB subgraph Input ["Packet Capture Layer"] A[Raw Network Traffic] --> B[Packet Processor] B --> C[Protocol Analyzer] end subgraph Core ["Analysis Engine"] D[Anomaly Detection] --> E[Threat Classification] E --> F[Alert Generation] subgraph ML ["Machine Learning Pipeline"] G[Feature Extraction] --> H[Pattern Recognition] H --> I[Behavioral Analysis] end C --> D F --> J[Alert Manager] end subgraph Output ["Response Layer"] J --> K[Real-time Alerts] J --> L[Metrics Dashboard] J --> M[Threat Reports] end classDef primary fill:#0a192f,stroke:#64ffda,stroke-width:2px,color:#fff classDef secondary fill:#172a45,stroke:#64ffda,stroke-width:2px,color:#fff classDef highlight fill:#233554,stroke:#64ffda,stroke-width:2px,color:#fff class A,B,C primary class D,E,F,J secondary class G,H,I,K,L,M highlight

Packet Capture Engine

Dynamic Batch Processing: Automatically adjusts batch sizes based on throughput and latency metrics
Zero-Copy Processing: Minimizes memory allocations using efficient packet handling
Worker Pool Management: Intelligent load balancing with performance tracking

Anomaly Detection System

Multi-dimensional Analysis: Considers multiple metrics simultaneously for accurate detection
Adaptive Thresholds: Dynamic threshold adjustment based on network patterns
Protocol-Specific Detection: Specialized algorithms for different protocols

Alert Management

Correlation Engine: Identifies related security events across time windows
Priority Assignment: Smart prioritization based on threat severity and context
Alert Enrichment: Automatic context addition from multiple data sources

Technical Capabilities

Packet Analysis Real-time packet capture and analysis with configurable batch processing

Memory Management Zero-copy packet processing with efficient memory allocation

Detection Capabilities Protocol-aware analysis with adaptive thresholds

Implementation Highlights

Concurrent Packet Processing

// Worker pool implementation with automatic scaling
type PacketProcessor struct {
    workers    []*Worker
    batchSize  atomic.Int32
    metrics    *Metrics
    // ... other fields
}

func (p *PacketProcessor) ProcessBatch(packets []Packet) {
    // Dynamic batch size adjustment based on metrics
    if p.metrics.Latency > threshold {
        p.batchSize.Store(p.batchSize.Load() / 2)
    }
    // ... processing logic
}