aaai-artifact-evaluati…
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without…
Use when deciding whether a security project fits ACM CCS versus IEEE S&P, USENIX Security, NDSS, PETS, or a crypto/theory venue, identifying the security contribution type, and sharpening the threat model and attacker capability before writing begins.
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill ccs-topic-selection --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/ccs-topic-selectionContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when deciding whether a security project fits ACM CCS versus IEEE S&P, USENIX Security, NDSS, PETS, or a crypto/theory venue, identifying the security contribution type, and sharpening the threat model and attacker capability before writing begins.
name: ccs-topic-selection description: Use when deciding whether a security project fits ACM CCS versus IEEE S&P, USENIX Security, NDSS, PETS, or a crypto/theory venue, identifying the security contribution type, and sharpening the threat model and attacker capability before writing begins.
Use this before writing. ACM CCS is the SIGSAC flagship: it rewards work with a concrete attacker, a defensible threat model, and evidence that survives an adversarial program committee. Decide venue by community and contribution type, never by prestige ranking.
a defense with measured cost, an applied-cryptography protocol, a systems or web-security mechanism, or a measurement study — aimed at the cross-area SIGSAC community.
systematization framing and the November cycle fits your calendar better.
evidence lives in a runnable tool and open benchmark.
routing, malware infrastructure).
its deployment, is the result.
| Signal in the project | CCS reading | |---|---| | New attack with a clearly bounded adversary and demonstrated impact | Core fit — the house genre | | Defense evaluated against adaptive attacks with deployment cost | Core fit | | Applied crypto protocol with implementation and measured overhead | Core fit | | Internet-scale or ecosystem measurement with validated sampling | Core fit | | Pure cryptographic hardness proof, no system | CRYPTO/EUROCRYPT or a theory venue | | Privacy-first metrics with no other security property | PETS/PoPETs |
A project extracts keys from a deployed TLS library via a microarchitectural side channel, with a proof-of-concept exploit and a constant-time patch. CCS reading: strong fit — a concrete attacker, measured leakage, and a defense with overhead numbers is exactly the CCS arc. Strip the exploit and keep only an abstract leakage bound, and it drifts toward a crypto theory venue; expand the network-measurement of vulnerable hosts into the whole story, and NDSS becomes plausible; foreground only the privacy harm to users, and PETS fits better.
write the threat model in three sentences, the contribution is not yet CCS-shaped.
because reviewers grade each against a different evidence bar.
needing 30 pages of proofs may belong at a journal or a theory venue.
final routing.
[Fit] strong CCS / possible CCS / better elsewhere [Best venue] CCS / IEEE S&P / USENIX Security / NDSS / PETS / crypto venue / other [Contribution type] attack / defense / protocol / measurement / tool / study [Threat model in one line] <adversary capability and goal> [Top rejection risk] <threat-model / novelty / evidence / ethics / scope> [Next action] <sharpen threat model, add evidence, reframe, or switch venue>
Stanford REAP × CoPaper.AI · 由斯坦福实证方法论团队精选与维护 访问 copaper.ai 微信:CoPaper.AI 按 11 个主流学科板块覆盖 经管与商科 社会科学 人文学科 数学与物理科学 生命科学 医学与健康 工程与技术 计算机科学与 AI 体育科学 点击任一学科名可跳转到对应说明;每类下的代表子领域在正文总览中完整列出。下方封面墙按 venue 导航,完整分类见覆盖一览。 🧭 布局指南 · 📚 Skill Pack 一览 · ⚡ 如何使用 · 🧪 自动实证
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