A framework for the visualization and generation of network traffic for the Internet of Things.
The following scenarios are pre-implemented:
The short paper "IoT dataset generation framework for evaluating anomaly detection mechanisms" by Andreas Meyer-Berg, Rolf Egert, Leon Böck, and Max Mühlhäuser for the general framework with its smart home scenario is available at https://doi.org/10.1145/3407023.3407036.
Clone the repository:
$ git clone https://git.tk.informatik.tu-darmstadt.de/SPIN/IoTDatasetGenerationFramework.git
Change to the directory:
$ cd IoTDatasetGenerationFramework
Build and run the project:
$ ./gradlew run
Gradle downloads these during the build process
Gradle will download required libraries and handle the build process
$ gradlew build # Assembles and tests this project
$ gradlew jar # Creates an executable Jar-file
$ gradlew javadoc # Generates Java Doc for the framework
$ gradlew test # Runs the included unit tests
$ gradlew run # Runs the IoTDatasetGenerationFramework as a JVM Application
$ gradlew runIt # Runs the IoTDatasetGenerationFramework as a Jar-file
$ gradlew tasks # Displays further available tasks
To change code of the framework, it is possible to import it into an IDE of choice (e.g., into Eclipse with File > Import > Gradle > Existing Gradle Project). Custom implementations of devices, protocols etc. can also be written in a separate project and later be imported.
For access to libraries during development the Jar files in "\build\install\SmartHomeNetworkSim\lib" can be imported. While running the framework, externally implemented programs can be imported.
Andreas T. Meyer-Berg (development as part of his Bachelor's Thesis)
Fabian Kaiser (data analysis, development, and evaluation as part of his Master's Thesis)
Leon Böck (initial idea and thesis supervision)