Hardware Design Dataset for Circuit Graph Analysis

Citation Author(s):
Rozhin
Yasaei
University of California Irvine
Shih-Yuan
Yu
University of California Irvine
Qingrong
Zhou
University of California Irvine
Mohammad Abdullah
Al Faruque
Mohammad Abdullah
Submitted by:
Rozhin Yasaei
Last updated:
Thu, 08/26/2021 - 14:23
DOI:
10.21227/j1vv-hw18
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Abstract 

The time-to-market pressure and the continuous growing complexity of hardware designs have promoted the globalization of the Integrated Circuit (IC) supply chain. However, such globalization also poses various security threats in each phase of the IC supply chain. Although the advancements of Machine Learning (ML) have pushed the frontier of hardware security, most conventional ML-based methods can only achieve the desired performance by manually finding a robust feature representation for circuits that are non-Euclidean data. As a result, modeling these circuits using graph learning to improve design flows has attracted research attention in the Electronic Design Automation (EDA) field. However, due to the lack of supporting tools, only a few existing works apply graph learning to resolve hardware security issues. We propose this dataset along with HW2VEC, an open-source graph learning tool that lowers the threshold for newcomers to research hardware security applications with graphs. HW2VEC provides an automated pipeline for extracting a graph representation from a hardware design in various abstraction levels (register transfer level or gate-level netlist). Besides, HW2VEC users can automatically transform the non-Euclidean hardware designs into Euclidean graph embeddings for solving their problems. This dataset includes the Verilog files of different hardware designs and the data-flow graphs that the HW2VEC tool is generated for each circuit.

If you find our dataset useful in your research, please kindly consider citing our papers:

@misc{yu2021hw2vec,

      title={HW2VEC: A Graph Learning Tool for Automating Hardware Security}, 

      author={Shih-Yuan Yu and Rozhin Yasaei and Qingrong Zhou and Tommy Nguyen and Mohammad Abdullah Al Faruque},

      year={2021},

      eprint={2107.12328},

      archivePrefix={arXiv},

      primaryClass={cs.CR}

}

Instructions: 

Refer to following resources:

HW2VEC Github

Technical Document