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Privacy-Enhancing Technologies Compared

Privacy-Enhancing Technologies Compared

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About this MicroSim

Four modern privacy-enhancing technologies are laid out as a 2x2 grid of cards, each described with the same six fields so they can be compared head to head: Homomorphic Encryption (FHE), Secure Multi-Party Computation (MPC), Differential Privacy (DP), and Zero-Knowledge Proofs (ZKP).

Every card answers the questions that actually drive a design decision: a one-line definition, who can see the inputs, who can see the outputs, the computational cost (visualized as a 1–5 bar that runs from rust to gold), and the technique's maturity (research, niche, or production). Reading down the cost column alone is revealing: differential privacy is cheap (1/5) while fully homomorphic encryption is expensive (5/5), which is why they show up in very different places.

Hover or tap any card for a real-world example — the U.S. 2020 Census for DP, Zcash for ZKP, threshold signatures for MPC, privacy-preserving ML inference for FHE. The amber footer band summarizes when to reach for which: each technique answers a different privacy question, so the goal is to match the tool to the requirement rather than defaulting to the most powerful (and most expensive) option.

Lesson Plan

Learning objective (Bloom: Analyze). Students will compare four privacy-enhancing technologies across the same six fields and select the appropriate technique for a given privacy requirement, justifying the choice with the input/output visibility and cost dimensions.

Suggested classroom use. Present three short scenarios — "publish neighborhood income statistics", "two hospitals study a shared cohort without sharing records", "prove you are over 18 without revealing your birthdate" — and have students name the best-fit technique and defend it using the card fields.

Discussion questions:

  1. DP and FHE sit at opposite ends of the cost scale. How does that cost difference explain where each one is actually deployed today?
  2. In MPC, every participant learns the output but not the others' inputs; in ZKP, only the verifier learns a true/false result. Why does that distinction matter when choosing between them?
  3. "Privacy" is not one property. For each technique, who exactly is being protected from whom?

References

Specification

The full specification below is extracted from Chapter 4: "Cryptography in Practice: PKI, TLS, and Data Protection".

Type: infographic-svg
sim-id: privacy-tech-compare
Library: Static SVG with hover tooltips
Status: Specified

A 2x2 grid of cards, each describing one technique with the same six fields:
header (technique name), one-line definition, inputs visible to whom, outputs
visible to whom, computational cost (1-5 bars), maturity, and a real-world example
in a hover tooltip.

Card 1 — Homomorphic Encryption (FHE): compute on ciphertext; inputs/outputs client
only; cost 5/5; maturity niche→production. Card 2 — MPC: parties compute jointly
without sharing inputs; cost 3/5; production. Card 3 — Differential Privacy: add
calibrated noise; cost 1/5; production. Card 4 — Zero-Knowledge Proofs: prove a
statement without revealing why; cost 4/5; production (growing).

A footer band lists "when to reach for which". Color: cybersecurity blue and slate
for headers, rust→gold gradient for the cost bars. Responsive: the SVG scales to its
container.