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This IDS focuses on detecting intrusion attempts by matching patterns in network data (such as suspicious strings in payloads or requests). It integrates the Knuth-Morris-Pratt (KMP) string-search algorithm for efficient pattern matching while also using auxiliary methods such as hashing and tries for indexing or rule-based detection.

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techy4shri/KMP-Intrusion-Detection-System

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KMP-Intrusion-Detection-System

This IDS focuses on detecting intrusion attempts by matching patterns in network data (such as suspicious strings in payloads or requests). It integrates the Knuth-Morris-Pratt (KMP) string-search algorithm for efficient pattern matching while also using auxiliary methods such as hashing and tries for indexing or rule-based detection.

This is an ongoing project and will be updated as I work on it.

Features

  • Efficient Pattern Matching: Utilizes the Knuth-Morris-Pratt (KMP) algorithm for fast and efficient string searching.
  • Auxiliary Methods: Incorporates hashing and tries for indexing and rule-based detection.
  • Real-time Detection: Capable of analyzing network data in real-time to detect intrusion attempts.
  • Modular Design: Easy to extend and integrate with other systems.

Installation

  1. Clone the repository:
    git clone https://github.com/yourusername/KMP-Intrusion-Detection-System.git
  2. Navigate to the project directory:
    cd KMP-Intrusion-Detection-System
  3. Install the required dependencies:
    pip install -r requirements.txt

Usage

  1. Run the main script to start the IDS:
    python main.py
  2. Configure the IDS by editing the config.json file to specify patterns and rules.

Contributing

This is a personal project and as such, no contributions are welcome at the moment.

License

This project is licensed under the MIT License. See the LICENSE file for details. (to be added)

Contact

For any questions or suggestions, please raise a new discussion.

About

This IDS focuses on detecting intrusion attempts by matching patterns in network data (such as suspicious strings in payloads or requests). It integrates the Knuth-Morris-Pratt (KMP) string-search algorithm for efficient pattern matching while also using auxiliary methods such as hashing and tries for indexing or rule-based detection.

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