OMNeT++ Vehicular Communication VeReMi Simulation

Project Objective:

Develop a simulation in OMNeT++ to generate the VeReMi dataset, which contains labeled vehicular communication data including both normal and malicious behaviors.

Implement realistic vehicle movement patterns and misbehavior models to create a dataset suitable for training misbehavior detection algorithms.

Key Requirements:

Software: Use OMNeT++, INET, and Veins for network simulation, with SUMO (Simulation of Urban MObility) for realistic traffic modeling.

External Libraries: Integrate the LuST (Luxembourg SUMO Traffic) scenario to simulate authentic urban traffic patterns within the OMNeT++ environment.

Misbehavior Models: Implement multiple types of misbehavior, such as false location reporting and message tampering, to simulate realistic attack scenarios in the dataset.

Simulation Setup:

Configure vehicle nodes in Veins to follow realistic mobility patterns provided by SUMO and the LuST scenario.

Set up communication parameters for vehicle-to-vehicle (V2V) interactions within the Veins framework.

Data Collection and Logging:

Log communication data, including timestamps, vehicle IDs, positions (both actual and tampered), and message content.

Ensure the dataset is structured with labels indicating normal and malicious behaviors for machine learning use.

Expected Deliverables:

Simulation Code: Fully functional OMNeT++ project setup, including Veins and SUMO integration.

Dataset: The generated VeReMi dataset, including labeled instances of normal and malicious vehicular data.

Documentation: Detailed setup instructions, explanations of misbehavior models, and a guide on how to replicate or modify the simulation.

Skills Required:

Proficiency with OMNeT++, Veins, and SUMO.

Experience in vehicular network simulations, especially with implementing malicious behavior in communication protocols.

Strong documentation skills to provide clear setup instructions and dataset descriptions.

The expected duration for the project is 1 - 2 days. Vehicle movement patterns should include basic traffic flow dynamics. Provide the essential setup instructions, an overview of the misbehavior models, and a brief guide to replicate the simulation. Include scenarios involving urban intersections. Provide detailed descriptions of the misbehavior models used. The traffic simulation should feature medium-detail visualization, with adequate visual representation of urban scenarios and behavior models. The traffic simulation should feature low-detail visualization, focusing on functionality over visual detail. The traffic simulation should feature low-detail visualization, focusing on functionality over visual detail.

C++ -ohjelmointi Simulation Python

Projektin tunnus: #38756434

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