Machine Learning

The PermGuard dataset is a carefully crafted Android Malware dataset that maps Android permissions to exploitation techniques, providing valuable insights into how malware can exploit these permissions. It consists of 55,911 benign and 55,911 malware apps, creating a balanced dataset for analysis. APK files were sourced from AndroZoo, including applications scanned between January 1, 2019, and July 1, 2024. A novel construction method extracts Android permissions and links them to exploitation techniques, enabling a deeper understanding of permission misuse.

The necessity for strong security measures to fend off cyberattacks has increased due to the growing use of Industrial Internet of Things (IIoT) technologies. This research introduces IoTForge Pro, a comprehensive security testbed designed to generate a diverse and extensive intrusion dataset for IIoT environments. The testbed simulates various IIoT scenarios, incorporating network topologies and communication protocols to create realistic attack vectors and normal traffic patterns.

M. Kacmajor and J.D. Kelleher, "ExTra: Evaluation of Automatically Generated Source Code Using Execution Traces" (submitted to IEEE TSE)

To provide machine learning and data science experts with a more robust dataset for model training, the well-known Palmer Penguins dataset has been expanded from its original 344 rows to 100,000 rows. This substantial increase was achieved using an adversarial random forest technique, effectively generating additional synthetic data while maintaining key patterns and features. The method achieved an impressive accuracy of 88%, ensuring the expanded dataset remains realistic and suitable for classification tasks.