Recommended Software Versions for paper: Tehrani, M.G., Sultanow, E., Buchanan, W.J., Amir, M., Jeschke, A., Houmani, M., Chow, R. and Lemoudden, M., 2024. Stabilized quantum-enhanced SIEM architecture and speed-up through Hoeffding tree algorithms enable quantum cybersecurity analytics in botnet detection. Scientific Reports, 14(1), p.1732.

Overview This README outlines the recommended software versions for a Quantum Machine Learning project. These versions are specified to ensure compatibility and optimal performance.

Python Version Python: 3.9 Python 3.9 is recommended for its stability and compatibility with the listed packages. Ensure your development environment uses Python 3.9.

Package Requirements The following packages and their specific versions are recommended:

Qiskit Machine Learning: 0.4.0 An extension of Qiskit for quantum machine learning applications. PyQuil: 4.0.0 A quantum computing library for writing and simulating quantum programs. Qiskit: 0.45 A fundamental library for quantum computing that provides tools to create and run quantum circuits. pip: >=22.3.1 The pip version 22.3.1 or higher is required for proper installation of the dependencies. NumPy: 1.26.2 Essential for scientific computing applied in the code. Matplotlib: 3.7.4 A library for creating static, animated, and interactive visualizations applied in visualization of results. SciPy: 1.11.2 Used for mathematics, science, and engineering applications. Scikit-Learn: 1.3.2 A tool for machine learning, providing various algorithms and tools for data mining and analysis applied in CBC for benchmark. Azure-quantum: <0.29.0 Microsoft Azure's service for quantum computing. Versions below 0.29.0 are recommended. Installation Ensure that your Python environment is set up correctly and that you have pip installed. You can install the packages using pip:

pip install qiskit==0.45 pip install qiskit_machine_learning==0.4.0 pip install pyquil==4.0.0 pip install numpy==1.26.2 pip install matplotlib==3.7.4 pip install scipy==1.11.2 pip install scikit-learn==1.3.2 pip install pylatexenc==2.10 pip install azure-quantum<0.29.0 Usage After installing the specified versions, you can import and use them in your Python projects as per your requirements.

Support For any issues or support related to these packages, please email madjid_tehrani@gwu.edu

Contributing For contributions or suggestions regarding this project's dependencies, please open an issue or pull request in the project repository.