Homomorphic encryption sounds like a universal calculator for ciphertext, but that was my first reaction to the term. The checklist tells me that’s not the case. The further I look, the more off it gets: the kinds of operations it supports are much fewer than you’d expect—so few that you can count them. So few that I counted them: just two and a half categories. When computing in encrypted state, is it truly an overall capability? I originally thought of it as one whole thing, but later I realized it should be read like a checklist—the answer is written in the checklist.
First, list the operation capabilities from the official materials, and verify item by item. Addition? Homomorphic addition works. Scalar multiplication? That works too. What about arbitrary multiplication? This section stumped me. I went through it three times and couldn’t find any corresponding supported entry. I spent 20 minutes getting to this point and then realized: homomorphic encryption isn’t an adjective—it’s a boundary table of capabilities. That’s the truth. Only what’s on the table can be computed. @Dusk
Break apart this boundary and see how it affects design trade-offs. If you want to do a computation on ciphertext, first ask one question: is that operation on the table? If it is, you compute directly in ciphertext. If it isn’t, you either decrypt first or switch to a different circuit design. Both paths have costs: the former exposes data, and the latter increases proof complexity—there are no free options. That’s an iron rule. Before choosing a path, make sure you’re clear about what cost your own data can tolerate.
45% to 255% is the slow range of WASM compared with native code—I checked this number twice. The publicity framing tells it as all-purpose encrypted computation, while the mechanism layer depicts a limited set of operations. The more I verify, the more tangled it becomes: ciphertext computation capability isn’t the same as universal computation. Most people only realize this difference when they finally look at the checklist. Where did the word “universal” come from? In the end, it only appears in the title— the truth is hidden in the title.
So when judging the quality of a privacy solution, don’t ask whether it has homomorphic encryption. Ask how many items are listed on its capability table. Some people think homomorphic encryption means universal computation, but I don’t see it that way. This is counterintuitive—the capability table is the only standard. If someone uses homomorphic encryption as an argument, $DUSK tell them to produce the table first. If they can’t produce it, just treat the word “universal” as if you never heard it. Reading the checklist takes only 5 minutes—that’s exactly the value. #dusk
First, list the operation capabilities from the official materials, and verify item by item. Addition? Homomorphic addition works. Scalar multiplication? That works too. What about arbitrary multiplication? This section stumped me. I went through it three times and couldn’t find any corresponding supported entry. I spent 20 minutes getting to this point and then realized: homomorphic encryption isn’t an adjective—it’s a boundary table of capabilities. That’s the truth. Only what’s on the table can be computed. @Dusk
Break apart this boundary and see how it affects design trade-offs. If you want to do a computation on ciphertext, first ask one question: is that operation on the table? If it is, you compute directly in ciphertext. If it isn’t, you either decrypt first or switch to a different circuit design. Both paths have costs: the former exposes data, and the latter increases proof complexity—there are no free options. That’s an iron rule. Before choosing a path, make sure you’re clear about what cost your own data can tolerate.
45% to 255% is the slow range of WASM compared with native code—I checked this number twice. The publicity framing tells it as all-purpose encrypted computation, while the mechanism layer depicts a limited set of operations. The more I verify, the more tangled it becomes: ciphertext computation capability isn’t the same as universal computation. Most people only realize this difference when they finally look at the checklist. Where did the word “universal” come from? In the end, it only appears in the title— the truth is hidden in the title.
So when judging the quality of a privacy solution, don’t ask whether it has homomorphic encryption. Ask how many items are listed on its capability table. Some people think homomorphic encryption means universal computation, but I don’t see it that way. This is counterintuitive—the capability table is the only standard. If someone uses homomorphic encryption as an argument, $DUSK tell them to produce the table first. If they can’t produce it, just treat the word “universal” as if you never heard it. Reading the checklist takes only 5 minutes—that’s exactly the value. #dusk