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Information Flow Paths from RTL Traces

arXiv Security Archived Jun 15, 2026 ✓ Full text saved

arXiv:2606.13860v1 Announce Type: new Abstract: Security validation is an important yet challenging part of the hardware design process, yet, by convention, validation engineers are tasked with defining the threat model, specifying the relevant security properties, detecting any violations of those properties, and assessing the consequences to system security, each of which is manually intensive and may introduce errors. The combined technologies of information flow tracking and specification mi

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    Computer Science > Cryptography and Security [Submitted on 11 Jun 2026] Information Flow Paths from RTL Traces Calvin Deutschbein, Owyn Wyatt Security validation is an important yet challenging part of the hardware design process, yet, by convention, validation engineers are tasked with defining the threat model, specifying the relevant security properties, detecting any violations of those properties, and assessing the consequences to system security, each of which is manually intensive and may introduce errors. The combined technologies of information flow tracking and specification mining represent an automated approach to property generation and validation, but prior work on information flow tracking on RTL trace data was limited to find cases under which information flowed between registers, without reproducing full paths to capture how sensitive information propagates through a design. With the introduction of new technologies accelerating hardware analysis, we develop a novel approach for constructing information flow paths from register transfer level (RTL) trace data. Comments: 9 pages, 3 figures, accepted and pending publication at INTCEC'26 Subjects: Cryptography and Security (cs.CR); Hardware Architecture (cs.AR) Cite as: arXiv:2606.13860 [cs.CR]   (or arXiv:2606.13860v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.13860 Focus to learn more Submission history From: Calvin Deutschbein [view email] [v1] Thu, 11 Jun 2026 19:41:04 UTC (211 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs cs.AR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Jun 15, 2026
    Archived
    Jun 15, 2026
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