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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.

Install / Use

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ccs-topic-selection

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

83/100

Category

Security

Supported Platforms

Universal

Our assessment of ccs-topic-selection

ccs-topic-selection scores 83/100 on our quality scale, 839th of 1,062 Security skills we index.

Its SKILL.md is 3.7 KB long, split into 6 sections with 1 code example: a solid amount of guidance for an agent.

With 1,158 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
15/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 18 days ago, so ccs-topic-selection is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

ccs-topic-selection compared with similar skills

All 4 of these similar skills score higher than ccs-topic-selection; compare them before choosing.

SkillScoreStarsUpdatedFormat
ccs-topic-selection (this skill)by brycewang-stanford831.2k18d agoSKILL.md
algorithmic-artby anthropics100177.9k10d agoSKILL.md
pptxby anthropics100177.9k10d agoSKILL.md
designby nextlevelbuilder100130.2k12d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k12d agoSKILL.md

Frequently asked questions

How do I install ccs-topic-selection?
Run npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ccs-topic-selection. The install tabs above show the steps for each supported agent.
Which AI agents does ccs-topic-selection work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is ccs-topic-selection safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is ccs-topic-selection still maintained?
The repository was last updated 18 days ago, so ccs-topic-selection is actively maintained.

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>

Related Skills

View on GitHub
GitHub Stars1.2k
CategorySecurity
Updated18d ago
Forks153

Languages

Stata

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions