Skills Data Science Open Science and Reproducibility in Research

Open Science and Reproducibility in Research

v20260724
usenixsec-reproducibility
This guide covers the mandatory Open Science appendix for high-level security research. It instructs authors on enumerating all artifacts (code, datasets, configurations), documenting data withholding decisions, and implementing engineering controls (like environment pinning and version tracking) to ensure that published results are independently and reliably reproducible.
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Overview

USENIX Security Reproducibility

Since the '26 cycle, USENIX Security has made openness a structural requirement: every submission carries an Open Science appendix stating where the artifacts behind the paper live, and acceptance is later conditioned on that availability verifying (Phase-1 AE). This skill covers the appendix itself and the underlying engineering that makes the statement true. Policy text is per-cycle — reread the current CFP section before relying on wording.

The Open Science appendix is a contract, not a caption

Reviewers read it during evaluation; the AEC enforces it after acceptance. It should answer, concretely:

  • What exists: code, datasets, configurations, analysis notebooks, hardware designs — enumerated, not gestured at.
  • Where: resolvable locations (anonymized mirrors at submission; permanent, ideally DOI-backed archives in the final paper).
  • What is withheld and why: the policy accepts justified omission, and security work legitimately generates a lot of it.
\section*{Open Science}
All scanner source code, the analysis pipeline, and the aggregated measurement
tables (Sections 4--6) are available at \url{<anonymized-archive>} and will be
deposited with a DOI upon publication. The raw scan captures contain
per-endpoint identifying data for still-unpatched hosts and are withheld;
Appendix~B documents the aggregation procedure so the tables can be
regenerated from an independent scan. The 214 disclosure emails are withheld
as human-subjects correspondence; templates are included.

Withholding decisions that hold up

Material Default posture Acceptable justification pattern
Attack/PoC code Share, targeted at a bundled testbed Weaponizable against unpatched population → share after patch window, state the date
Vulnerability details Share post-disclosure Coordinated disclosure incomplete → embargo with timeline in the Ethical Considerations appendix
Scan/measurement raw data Share aggregated Raw data identifies vulnerable hosts or users → aggregate + publish the aggregation code
User-study transcripts Withhold; share instruments IRB/consent scope → release codebooks, surveys, and quantitative summaries
Malware corpora Hashes + provenance Redistribution illegal or dangerous → document acquisition path others can follow
Vendor-provided datasets As NDA allows Contract limits → say so and provide synthetic or public-subset substitutes

Two disciplines make these defensible: decide them at experiment time (retrofit justifications read as excuses), and always ship the procedure even when the data stays closed — an independent team with their own vantage point should be able to re-derive your tables.

Determinism engineering for security experiments

Security results are unusually time- and environment-coupled. Pin what you can and timestamp what you cannot:

  • The internet moves. Record scan dates, target-list snapshots, and blocklist versions; a reproduction in 2027 measures a different network than 2026 did.
  • Fuzzing and probabilistic attacks: fix seeds where the harness allows, and report distributions over repeated campaigns (count, median, IQR) rather than a best run; state the compute budget per campaign.
  • ML-based pipelines (classifiers, LLM-assisted analysis): pin model versions and weights; a hosted-API dependency is a reproducibility hole — snapshot outputs and say so.
  • Version-sensitive exploits: record exact kernel/firmware/browser builds, and keep the vulnerable version archived in the artifact since upstream will patch.
# Capture the environment fingerprint alongside every experiment run
{ date -u +%FT%TZ; uname -srmo; git rev-parse HEAD;
  sha256sum targets.txt config.yaml; pip freeze | sort; } > runs/$(date +%s).env

Paper-side reporting that reviewers check

  • Every headline number traces to a script in the artifact; the claims table in the artifact README (see usenixsec-artifact-evaluation) is the index.
  • Ranges and repetition counts for stochastic results; single-run numbers flagged as such.
  • Dataset construction fully specified: collection window, filters, dedup rules, ground-truth labeling procedure and inter-rater agreement where humans labeled.
  • Negative-result honesty: configurations where the attack fails or the defense costs too much belong in the paper, and reviewers at this venue notice absence.

Reverify each cycle

  • Exact Open Science appendix requirements and page allowance in the current CFP.
  • Whether availability verification remains acceptance-conditional ('27 待核实).
  • Current AEC guidance on acceptable archives and anonymized hosting.

Output format

[Inventory] artifacts enumerated: code / data / configs / instruments
[Open items] each withheld artifact + justification + procedure substitute
[Determinism] seeds, environment fingerprints, time-coupling documented
[Trace] headline claims ↔ regeneration scripts: n/m covered
[Appendix draft] Open Science text ready: yes / gaps listed
Info
Category Data Science
Name usenixsec-reproducibility
Version v20260724
Size 5.39KB
Updated At 2026-07-29
Language