Evidence at NDSS answers one question: would this hold on the real network? Every design choice in the evaluation — target selection, vantage, scale, baseline — either supports that answer or advertises that you avoided it.
| You claim... | Reviewers require... | Weak substitute they will flag |
|---|---|---|
| A new attack | End-to-end demonstration on real implementations, named versions, measured preconditions and cost | PoC against a config you weakened |
| A prevalent condition | Defined population, sampling method, validated vulnerability test, false-positive analysis | Extrapolation from anecdotes |
| A defense | Security and utility: adaptive-adversary evaluation + overhead on realistic workloads | Blocking only the published attack |
| A detection system | Base-rate honest metrics on traffic resembling deployment, drift discussion | Accuracy on one stale benchmark |
| A protocol change | Interop and incremental-deployment story, behavior under partial adoption | "Assume everyone upgrades" |
Match the substrate to the claim, and say why in the paper:
Mixed designs are the norm: demonstrate on real systems, generalize on the testbed, sweep in emulation, and keep the chain of custody between the three explicit.
For defenses, the reviewer's first move is to play attacker against your design. Do it first, in print:
Live experiments are bounded by harm, and the CFP backs this with an Ethics Review Board. Design limits in from the start: rate caps and opt-out honoring for scans, no serving of real user traffic during interception experiments, synthetic victims wherever the demonstration allows, notification pipelines for anything you confirm exploitable, and IRB engagement where humans are observed — while remembering NDSS treats IRB sign-off as necessary context, not sufficient mitigation. Every one of these choices belongs in the paper's method text, not only in the ethics section.
For every headline number, the text or appendix must pin:
target set + versions + selection method
vantage(s) and observation window
trials, variance, and the aggregation rule
hardware/software of the measurement or attack host
configuration deltas from defaults (ideally: none, or justified)
the command or procedure that regenerates the number (→ artifact)
Numbers that move between runs get intervals; comparisons against baselines get identical conditions or an explanation of why identity was impossible.
[Claim → evidence map] each headline claim + substrate + status
[Adaptive evaluation] strategies enumerated / strongest implemented / result
[Measurement validity] population, vantage, validation, error directions
[Ethics parameters] rate caps, synthetic victims, notification, IRB state
[Repro pinning] items from the reporting block still missing