NALA
NETWORK AI LOG-BASED ANALYZER

Real-Time AI Detection of Botnets, Malware and Network Threats

By:

Havi Lead Security Engineer

Overview

AI-based, open-source tool for detecting and blocking network backdoors in real time.

Problem

Stealthy Threats

Traditional tools miss backdoors

Slow Detection

Legacy systems can't keep up in real-time

High Costs

Advanced security breaks the bank

Complexity

Hard to deploy and maintain

Our Solution

An open-source, AI-powered security solution that's powerful yet simple to use

Goals & Objectives

The project aims to improve threat detection and simplify response through AI.

Project Scope

Defining the boundaries and deliverables of our AI-powered network security solution

Included

  • AI engine for detecting network anomalies
  • Real-time log and traffic analysis
  • Web and mobile monitoring interfaces
  • Integration with Suricata and Splunk
  • Deployment on Raspberry Pi 5

Excluded

  • Manual threat analysis workflows
  • Proprietary software components
  • On-premise AI model training

Work Breakdown Structure

  • 1. Planning & Requirements Gathering
  • 2. Prototype Development (Engine + Dataset)
  • 3. Detection Module & Parser
  • 4. Tool & System Integration
  • 5. UI Development
  • 6. Testing & Validation
  • 7. Deployment & Documentation

Excluded:

Timeline & Milestones

  • • Nov 2024 – Project Initiation
  • • Jan 2025 – Requirements Finalized
  • • Mar 2025 – Prototype Complete
  • • May 2025 – UI & Integration Ready
  • • Jul 2025 – Testing Completed
  • • Aug 2025 – Final Deployment
  • • Sep 2025 – Project Closure

Budget Estimation

Total Budget (Target): $10,000
Actual Estimate: $11,330

Main Costs:

  • • Cloud AI Training: $6,000
  • • Deployment Hardware (Raspberry Pi): $750
  • • Local AI Setup: $2,000
  • • Tools, Licenses, Security: $780
  • • Compliance & Monitoring: $750
  • • Contingency: $700

Efficient use of open-source tools and low-cost hardware kept costs within a manageable range.

Resource Planning

People

  • • Lead Security Engineer
    (design, deployment)
  • • AI Engineer
    (model training, validation)
  • • Frontend Developer
    (UI/dashboard)
  • • DevOps & IT Admins
    (integration, testing)

Tools & Platforms

  • Development: Python, Flask, Electron
  • Networking: Suricata, tcpdump, Wireshark
  • Virtualization: VMware, Proxmox, QEMU
  • DevOps: Git, CI/CD, Raspberry Pi 5

Risk Assessment

Top Risks & Mitigation Strategies

1

Insufficient Training Data

→ Use synthetic/public datasets
→ Simulate logs for better coverage
3

Legacy System Compatibility

→ Design flexible APIs
→ Use wrappers/adapters
5

Stakeholder Resistance

→ Emphasize ease of use
→ Highlight cost-effectiveness
2

Hardware Limitations

→ Optimize processing
→ Offload to cloud
4

Budget Constraints

→ Phase-based deployment
→ Open-source solutions

Stakeholder Analysis

Key stakeholders and their engagement strategies for successful project implementation

Primary Stakeholders

  • Havi

    Project Lead

  • S-STEM

    Sponsor

  • SOC Analysts / IT Admins

    End Users

Engagement Strategy

  • Manage Closely

    Havi , S-STEM, Clients

  • Keep Satisfied

    CISOs, Compliance Officers

  • Keep Informed

    SOC teams, IT staff, Vendors, Universities, Open-source Community

Reflection & Lessons Learned

Successes
Challenges
Improvements

For more information, visit our website:

Here!