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ZENODO
Software . 2026
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2026
Data sources: ZENODO
ZENODO
Software . 2026
Data sources: Datacite
ZENODO
Software . 2026
Data sources: Datacite
ZENODO
Software . 2026
Data sources: Datacite
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Software Suite for "Hardware Trojans from Invisible Inversions: On the Trojanizability of Standard Cell Libraries"

Authors: Dorschel, Kolja; Plätz, Lukas; Walendy, René; Moos, Thorben; Paar, Christof; Becker, Steffen;

Software Suite for "Hardware Trojans from Invisible Inversions: On the Trojanizability of Standard Cell Libraries"

Abstract

This artifact accompanies our paper "Hardware Trojans from Invisible Inversions: On the Trojanizability of Standard Cell Libraries", published at IEEE S&P 2026. It contains the implementation of our via-position-based similarity metric and Trojan detection pipeline, along with preprocessed data enabling reproduction of the paper's main claims. The artifact operates on the publicly available backside SEM dataset of Puschner et al. (S&P 2023), covering four CMOS technology nodes (90 nm, 65 nm, 40 nm, and 28 nm). It includes methods for via extraction (including persistence-based detection), construction of cell-type representatives, pairwise similarity scoring of functionally distinct cell types, and Trojan detection. Preprocessed intermediate results are provided to facilitate artifact evaluation without requiring the full multi-day preprocessing pipeline from scratch; a proof-of-concept of the preprocessing is included in the Jupyter notebook. The three main claims supported by the artifact are: (1) cells in the 28 nm technology node are substantially more similar than in 40 nm, 65 nm, and 90 nm technologies, (2) our via-position metric strongly outperforms baseline detection methods on the most similar cell pairs, and (3) our method detects all Trojans from the original experiment of Puschner et al., including in the 28 nm node where prior work reported false negatives. Software, instructions, and further details can be found in the GitHub repository at the following URL: https://github.com/emsec/DAFT

Keywords

Hardware Reverse Engineering, Hardware Trojans, Hardware Security

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average