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

2025/05/09 by Calvin Deutschbein, Deutschbein, Calvin, Jimmy Ostler +3
Computer Science · #Advanced Malware Detection Techniques #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Hardware Architecture (cs.AR)

paper · doi:10.48550/arxiv.2505.06470

openalex publication_date 2025/05/09 · openalex created_date 2025/10/15 · openalex updated_date 2026/07/28

Abstract

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 researchers via GitHub and Colab.

Citations

• Assessing the Performance of OpenTitan as Cryptographic Accelerator in Secure Open-Hardware System-on-Chips
• AKER: A Design and Verification Framework for Safe andSecure SoC Access Control
• Spectre Attacks: Exploiting Speculative Execution
• Spectre attacks
• The Daikon system for dynamic detection of likely invariants
• MapReduce

Related

• RTL-Breaker: Assessing the Security of LLMs against Backdoor Attacks on HDL Code Generation
• CHARGE: Leveraging CWE Hierarchies for Hardware Security SystemVerilog Assertion Generation
• Evolutionary Large Language Models for Hardware Security: A Comparative Survey
• Technical Report for HW2VEC -- A Graph Learning Tool for Automating Hardware Security
• Security Properties for Open-Source Hardware Designs