F2MD is a VEINS Module.
This project is open source and available on github.
This framework provides complete solution for real time simulation and evaluation of a MisBehavior Detection (MBD) system. It extends VEINS with a large panel of MBD, evaluation and other general Cooperative Intelligent Transport Systems (C-ITS) modules. One of the main characteristics of F2MD is its modularity. The architecture is organized in several functional levels: input data, local detection, local visual output, report data output and global detection. According to the misbehavior evaluation level, the complexity of the scenario, the attacks and the detection method may be chosen. Additionally, F2MD is extensible. Besides the implemented MBD mechanisms and attacks, it offers the possibility to extend the framework with additional modules through the existing API. A key characteristic of our framework is its integration with non-simulated modules such as external Machine Learning modules for advanced MBD and external packet reporting logging.
F2MD provides a singular framework with which one can:
- Evaluate effectiveness of attacks
- Assess performance of MBD algorithms
- Implement new attacks and MBD algorithms for easy comparison
- Visualize in real-time the MBD algorithms performance
- Generate attacks datasets
- Evaluate multiple misbehavior report formats
- Evaluate global misbehavior detection algorithms
F2MD Technical Modules:
- Basic Plausibility Checks on Received Beacons (mdChecks)
- Node Level Plausibility Investigation (mdApplications)
- Real Time Machine Learning for Plausibility Investigation (HTTP to a Python Server: PyMLServer-Local)
- Real Time Detection Status Output (mdStats)
- Support for Multiple Reporting Mechanisms (mdReport)
- Support for Global Reports Collection and Investigation (HTTP to a Python Server: MAServer-Global)
- Some Basic Pseudonym Change Policies (mdPCPolicies)
- Some Local and Global Misbehavior Attacks Implementation (mdAttacks)