Skill UI

This comprehensive guide details the strict content partitioning rules for preparing papers for top-tier security conferences like IEEE S&P. It advises authors on differentiating between core claims (which must live in the limited body pages) and verification material (which belongs in the appendix), ensuring adherence to strict page limits and review expectations.

This guide helps researchers evaluate whether a security or privacy project is a suitable fit for top-tier academic conferences like IEEE S&P. It covers critical fit tests, such as establishing a defensible threat model and ensuring end-to-end evidence closure. It also provides advice on SoK paper formats, routing among major security venues (USENIX, CCS, NDSS), and adhering to submission rules like one-year embargoes.

A comprehensive guide for positioning security research submissions (e.g., for NDSS, USENIX). It teaches how to write the 'Related Work' section not as a mere literature review, but as a critical security argument that establishes genuine novelty (the 'delta') by distinguishing mechanisms, layers, and preconditions from prior art. Covers citation verification, handling concurrent work, and double-blind anonymity rules.

This comprehensive guide outlines the rigorous, multi-stage submission process for USENIX Security Symposium papers. It covers mandatory formatting rules, including the 13-page main body and required appendices for Ethical Considerations and Open Science. The guide also details critical steps for maintaining double-blind anonymity, managing complex HotCRP deadlines, and avoiding early rejection pitfalls.

A rigorous guide for drafting high-stakes, technical security papers for the USENIX Security Symposium. It mandates a threat-model-first structure, requiring authors to quantify all security claims with measurable data to avoid hyperbole. The guide also details integrating responsible disclosure narratives and adhering to strict academic formatting rules.

Provides a comprehensive framework for blue-team threat hunting and detection engineering. Users learn hypothesis-driven hunting techniques, optimize SIEM queries, and build robust detection rules using industry standards like Sigma and YARA. Essential for minimizing false positives and validating security controls in a defensive posture.