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🔐 Envirm: Smart Security & IoT Ecosystem

The envirm organization hosts a collection of repositories that collaboratively form an integrated system aimed at enhancing device and network security through AI-driven analysis, IoT integration, and user-friendly interfaces.​

📦 Repository Overview

1. Network-Packet-Analyzer

Language: Python​

Description: Simulates a firewall and intrusion detection system (IDS) that processes incoming network packets, identifies potential threats, and logs incidents.​

Functionality:

  • Analyzes packet metadata (e.g., IP addresses, ports, protocols).​

  • Detects threats such as port scans, DDoS attacks, and malware.​

  • Maintains a list of blocked IPs and logs all decisions.​

  • Exposes RESTful endpoints for integration with front-end applications.​

2. AI-Service

Language: Python

Description: Implements AI models for threat detection and analysis, providing intelligence to the Network-Packet-Analyzer.​

Functionality:

  • Processes network data to identify anomalies.​

  • Classifies traffic patterns and potential threats.​

  • Outputs threat assessments with confidence scores.​

3. Locken-Mobile

Language: Dart​

Description: A mobile application designed to manage access to smart locks, integrating AI for enhanced security.​

Functionality:

  • Controls smart lock mechanisms.​
  • Utilizes AI for user recognition and authentication.​
  • Provides real-time access logs and notifications.​

4. locken-block

Language: Go​

Description: Backend service supporting the Locken-Mobile application, handling secure communications and device management.​

Functionality:

  • Manages smart lock states and user permissions.​
  • Ensures secure data transmission between devices and the mobile app.​

5. tracken-iot

Language: C++​

Description: Firmware for IoT devices that monitor and report on environmental and security-related metrics.​

Functionality:

  • Collects data from sensors (e.g., motion, temperature).​
  • Communicates with central servers for data analysis.​
  • Triggers alerts based on predefined security thresholds.​

6. envi-front

Language: TypeScript​

Description: Front-end application providing a dashboard for administrators to monitor and control the security ecosystem.​

Functionality:

  • Displays real-time data from various system components.​
  • Allows management of blocked IPs and review of threat logs.​
  • Facilitates configuration of system settings and thresholds.​

7. Hyperledge-Gateway

Language: TypeScript​

Description: Acts as a gateway for integrating blockchain technology into the security system, ensuring data integrity and transparency.​

Functionality:

  • Records security events on a blockchain ledger.​
  • Provides verifiable audit trails for security incidents.​
  • Enhances trust in the system's data handling processes.​

8. Face-classification-using-CLIP

Language: Python

Description: Demonstrates facial classification using OpenAI's CLIP model, potentially for biometric authentication within the security system.​

Functionality:

  • Processes facial images to identify individuals.​
  • Integrates with access control mechanisms for user verification.​

🧩 System Architecture

The Envirm ecosystem is designed with modularity in mind, allowing each component to function independently while contributing to the overall security infrastructure.​

Data Flow

  • IoT devices (tracken-iot) collect environmental and security data.​
  • Data is sent to the Network-Packet-Analyzer for initial processing.​
  • The AI-Service analyzes data for potential threats.​
  • Identified threats are logged and, if necessary, IPs are blocked.​
  • Administrators interact with the system via the envi-front dashboard.​
  • Access control is managed through Locken-Mobile and locken-block.​
  • All critical events are recorded on the blockchain via Hyperledge-Gateway.

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