External Adversary-Based Localisation of Network Topology and Intrusion Detection System in UW-ASN

Project Overview

This repository contains the implementation of the research project titled "External Adversary-Based Localisation of Network Topology and Intrusion Detection System in UW-ASN". This study addresses the security vulnerabilities in Underwater Acoustic Sensor Networks (UW-ASNs) by investigating how external adversaries can localise network nodes and improve the strategic deployment of Intrusion Detection Systems (IDS) for enhanced security.

Features & Objectives

• Network Simulation – Simulating UW-ASNs using NetSim v14.1.
• Topology Analysis – Identifying network structure vulnerabilities.
• IDS Deployment – Strategic positioning of IDS for optimal security.
• Adversarial Threat Modelling – Assessing potential attack vectors.
• Machine Learning for Localisation – Implementing clustering & signal-based positioning techniques.

Project Structure

├── docs/                         # Documentation and reports
│   ├── images/                   # Contains network topology, IDS placement, and result visualizations
│   ├── reports/                   # Research findings and analysis reports
├── src/                          # Source code directory
│   ├── pre_processing/           # Scripts for cleaning and structuring raw data
│   ├── prediction/               # Machine learning models for threat localization
├── data/                         # Dataset directory
│   ├── processed/                # Preprocessed data ready for model input
│   ├── raw/                      # Raw dataset files including sensor logs and adversary positions
├── model/                        # Model configurations, constants, and file paths
├── README.md                     # Project documentation
├── main.py                       # Main script to execute the full pipeline
├── requirements.txt              # Required dependencies for setup

Installation & Setup

Prerequisites

• Python 3.11+
• NetSim Standard v14.1 Licensed
• Visual Studio (for C++ based network simulation modifications)
• PyCharm

Setup Instructions

1. Clone the repository:

   git clone [https://github.com/yourusername/uwasn-security.git
   cd uwasn-security](https://github.com/Vivek-Tate/IDS-Detection-and-Exploiting-Vulnerabilities-in-UWAN.git)

2. Install dependencies:

   pip install -r requirements.txt

Datasets & Analysis

Acoustic Measurements File

• Contains logs of packets intercepted by adversary nodes.

Device Properties File

• Provides coordinates of adversary nodes for localisation.

Technical Implementation

• Network Simulation: Utilizes NetSim v14.1 with a modified C++ based DBR protocol.
• Topology Analysis: Implements RSSI-based distance estimation and trilateration.
• IDS Deployment: Leverages DBScan clustering for optimized security node placement.
• Threat Modelling: Assesses passive adversary capabilities through network interception.

Results & Key Findings

• Node localisation accuracy improved from ~15% to ~65% using a hybrid approach.
• Strategic IDS placement significantly reduces undetected threats.
• Low false positives in adversary detection using optimised clustering techniques.

License

See the LICENSE file for details.

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Feel free to reach out via the project's GitHub repository for any issues or contributions. Enjoy exploring!