Technical Documentation
A comprehensive overview of the SurakshaAI Integrated Defense Intelligence System.
1. Project Overview
1.1 Problem Statement
Suraksha AI addresses critical defense and strategic challenges facing Pakistan's national security infrastructure by providing AI-driven solutions for real-time cybersecurity threat intelligence, intelligent video surveillance, automated border anomaly detection, and multi-modal threat assessment.
1.2 Target Beneficiaries
Primary beneficiaries include the Pakistan Armed Forces, government cybersecurity teams, critical infrastructure operators, and law enforcement agencies.
1.3 Unique Value Proposition
- Resource Optimization: Lightweight models optimized for deployment in resource-constrained environments.
- Multi-modal Integration: Unified platform combining cyber and physical threat detection.
- Localized Training: Models fine-tuned on Pakistan-specific threat patterns and scenarios.
- Offline Capability: Core functions operational without constant internet connectivity.
2. Technical Modules
3. Performance Metrics
Quantitative performance indicators for each module.
| Module | Metric | Value | Benchmark |
|---|---|---|---|
| Threat Intelligence - Cyberattack | Accuracy | 88% | 85% |
| Threat Intelligence - Cyberattack | Precision | 85% | 82% |
| Threat Intelligence - Cyberattack | Recall | 83% | 80% |
| Threat Intelligence - Cyberattack | F1-Score | 84% | 81% |
| Threat Intelligence - Phishing | F1-Score | 90% | 87% |
| Threat Intelligence - Phishing | False Positive Rate | 8% | 12% |
| Video Surveillance | mAP@0.5 | 75% | 72% |
| Video Surveillance | Processing Speed | 30 FPS | 25 FPS |
| Video Surveillance | Precision (Vehicles) | 78% | 75% |
| Border Anomaly | Drone Detection Recall | 92% | 90% |
| Border Anomaly | Person Detection Accuracy | 85% | 83% |
| Border Anomaly | False Alarm Rate | <5% | <10% |
4. Technical Environment
Hardware Requirements
Minimum Configuration
- CPU: Intel Core i5 (8th Gen)
- RAM: 16 GB DDR4
- GPU: NVIDIA GTX 1660 (6GB VRAM)
Recommended Configuration
- CPU: Intel Core i7 (10th Gen)
- RAM: 32 GB DDR4
- GPU: NVIDIA RTX 3060 (12GB VRAM)
Core Software Dependencies
# Core Dependencies python==3.9.0 fastapi==0.118.2 uvicorn[standard]==0.37.0 # Data Processing numpy==1.26.4 pandas==2.2.3 scikit-learn==1.7.2 # Deep Learning - Core torch==2.6.0+cu118 torchvision==0.21.0+cu118 # Deep Learning - Transformers transformers==4.57.0 # Computer Vision ultralytics>=8.0.0 opencv-python>=4.8.0 # Web Frameworks gradio==5.23.0 streamlit==1.28.0
5. Team Information (Cyber4ce)
The team behind SurakshaAI from NUML, Islamabad.
Salman Khan
Team Lead, Ai Engineer + Front End
Deep Learning, React, Firebase, Cybersecurity
codewithsalty@gmail.comIqra Khan
Data scientist
Object Detection, Computer Vision, Border Anomaly Analysis
iqra27863@gmail.com