Publication of a High-Impact Scientific Research Paper in a Prestigious International Journal
Two faculty members from the Department of Computer Science at the College of Science of our university have successfully published a high-level scientific research paper in the fields of cyberattacks (hacking) and artificial intelligence (AI) within a renowned international impact-factor journal.
Mr. Karwan Mahdi Hama-Rauf (Lecturer) and Mr. Brwa Rahim (Assistant Lecturer), both faculty members in the Computer Science Department, published their co-authored study titled:
"ASCA-Net: Deep Learning-Based Acoustic Side-Channel Attack System for Keystroke Recognition Across Multiple Platforms"
The paper has been published in the Journal of Computer Virology and Hacking Techniques, which features an Impact Factor of 2.7, a CiteScore of 6.6 (Q2), and is published by the prestigious global publisher Springer.
Research Abstract
This study introduces a novel AI-driven system named ASCA-Net, which utilizes artificial intelligence to recognize and deduce typed text solely from the acoustic sounds of keyboard strokes. Remarkably, the system remains highly effective even when the audio is captured and transmitted through popular communication platforms like Zoom and Messenger.
The experimental results show that the system achieved an outstanding accuracy rate of 99.87% in local testing environments and 96.97% over Voice over IP (VoIP) audio. These findings demonstrate that typing alone does not guarantee complete data privacy unless proper security measures and countermeasures against keyboard acoustic recordings are implemented. This research marks a significant step forward in understanding the threats posed by Acoustic Side-Channel Attacks and developing modern data security and privacy protection protocols in digital workspaces.
With this breakthrough, this study becomes another prominent addition to the three consecutive papers previously published by our university's researchers in this specific domain. Other researchers can leverage these findings to increase awareness and defend against audio-based cyberattacks through the development and optimization of precise artificial intelligence models.
- Research Link: Springer Link
- Journal: Journal of Computer Virology and Hacking Techniques