Use when planning an ACM CCS project timeline across the two HotCRP review cycles, from venue fit through abstract registration, full-paper upload, rebuttal, notification, revision, artifact evaluation, ACM camera-ready, and in-person presentation, with backward-planning offsets and the security big-four deadline-hopping calendar.
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Use this as the project-management skill for a CCS submission. CCS is a conference, not a journal: it has no editor-in-chief and no article-processing charge. The rotating leadership is the per-edition General Chairs and Program Co-Chairs (CCS 2026 Program Co-Chairs: Véronique Cortier and Zhiqiang Lin, reported 2026-07-08; verify against the organizing-committee page). Replace every date below with the current cycle's HotCRP deadlines and work backward.
CCS runs two review cycles per year into one conference. A paper enters one cycle only; work rejected in the first cycle may not be resubmitted (even revised) to the second cycle of the same year. Pick the cycle from readiness, not hope — a thin first-cycle submission burns the year at this venue.
| Weeks out (heuristic) | Attack-plus-defense milestone |
|---|---|
| 10+ | Threat model frozen, attack primitive working end to end |
| 8 | Defense implemented; adaptive attacker designed against it |
| 6 | Measurement or evaluation runs complete, environment logged |
| 4 | Ethics and responsible-disclosure section drafted, disclosure initiated |
| 3 | Full draft in ACM sigconf two-column format |
| 2 | Internal red-team read by an adversarial-minded colleague |
| 1 | Anonymity sweep, artifact-availability statement, appendix assembly |
| 0 | Abstract registered, then full paper in HotCRP |
Anchor every offset to the current cycle, never to a past calendar.
CCS, IEEE S&P, USENIX Security, and NDSS run rolling multi-cycle deadlines, so a paper rejected in one can often be reworked into the next open venue within weeks. Keep a live map: a CCS Cycle A reject in April can target USENIX Security or the next NDSS cycle rather than waiting a year. Never resubmit unchanged — reviewers rotate across all four venues.
[Current stage] idea / building / writing / abstract / submission / rebuttal / accepted / artifact
[Cycle] A / B and next official deadline (date + source, or unknown)
[Critical path] <three tasks that determine readiness>
[Risk register] <threat-model / anonymity / ethics / evidence / artifact / presentation>
[Owner map] <task -> person or role>
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Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
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Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
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Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
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Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
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Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
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Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
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