"vcd2df" - Leveraging Data Science Insights for Hardware Security Research

In this work, we hope to expand the universe of security practitioners of open-source hardware by creating a bridge from hardware design languages (HDLs) to data science languages like Python and R through novel libraries that convert VCD (value change dump) files into data frames, the expected input type of the modern data science tools. We show how insights can be derived in high-level languages from register transfer level (RTL) trace data. Additionally, we show a promising future direction in hardware security research leveraging the parallelism of Spark to study transient execution CPU vulnerabilities, and provide reproducibility resources via GitHub<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> and Colab<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>.