Abstract
As cyberattacks grow in frequency and sophistication, digital forensics has become essential for enhancing network security and facilitating timely incident response. This article provides a comprehensive evaluation and demonstration of the practical use of Velociraptor, an open-source digital forensics and incident response tool, for efficient evidence collection and analysis in large-scale network environments. The study highlights how Velociraptor, through its customizable Velociraptor Query Language (VQL), significantly improves the speed, accuracy, and scalability of forensic investigations. A comparative analysis with established forensic tools underscores Velociraptor’s advantages in automating real-time data collection, flexible configuration, and large-scale deployment. In addition to discussing challenges such as the tool’s steep learning curve and resource demands, the article explores opportunities for further enhancement through artificial intelligence integration and performance optimization. The findings suggest that Velociraptor is a powerful asset for modernizing digital forensics and strengthening network security strategies.
Published Version
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