Skip to content
Content
Skill

/ccs-topic-selection

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.

From plugin
awesome-journal-skills
965200 skills
Install
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill ccs-topic-selection --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/ccs-topic-selection

Context 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.

SKILL.md

ccs-topic-selection.SKILL.md
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.

CCS Topic Selection

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.

Fit test

  • Prefer CCS when the contribution is a broad computer-security result — a new attack class,

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.

  • Route to IEEE S&P (Oakland) when the work suits that PC's taste for foundational or

systematization framing and the November cycle fits your calendar better.

  • Route to USENIX Security when the contribution is artifact-heavy systems security whose

evidence lives in a runnable tool and open benchmark.

  • Route to NDSS when the core is network- and distributed-system security (protocols, DNS,

routing, malware infrastructure).

  • Route to PETS/PoPETs when privacy is the primary lens rather than one property among many.
  • Route to CRYPTO/EUROCRYPT when the contribution is cryptographic theory whose proof, not

its deployment, is the result.

Fit signal table

| 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 |

Vignette: where a side-channel result goes

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.

Sharpening moves before committing

  • Name the attacker: capabilities, knowledge, position, and what success means. If you cannot

write the threat model in three sentences, the contribution is not yet CCS-shaped.

  • Decide the contribution type — attack, defense, protocol, measurement, tool, or study —

because reviewers grade each against a different evidence bar.

  • Confirm the result fits the 12-page ACM sigconf body; CCS bodies are dense, and a paper

needing 30 pages of proofs may belong at a journal or a theory venue.

  • Scope drifts across cycles; scan the current CFP topic list and recent proceedings before

final routing.

Output format

[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>
Read more
Ships withawesome-journal-skills

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

Get the whole plugin
Stats
965
Stars
121
Forks
Active
Maintenance
Stata
Language
MIT
License
13h ago
Last commit
2mo ago
Created

Repo: brycewang-stanford/Awesome-Journal-Skills

Other skills on awesome-journal-skills.