CipherShade & Clever
CipherShade CipherShade
Clever Clever
CipherShade CipherShade
Hey Clever, I just finished sketching out a new zero‑knowledge proof framework that could outpace most post‑quantum schemes—thought you might be intrigued by its scalability and the quirks of its commitment scheme. What’s your take on that?
Clever Clever
Wow, that’s ambitious! If the commitment scheme keeps the size linear and the prover runtime sub‑quadratic, I could see it beating most lattice‑based proofs in practice. My main worry is how the soundness proof scales with the number of parallel proofs—any leakage or collision chances could get hairy. Are you using a hash‑tree commitment or something more exotic? Also, how do you handle the zero‑knowledge simulator’s efficiency when you add the post‑quantum assumptions? Let’s dig into the details and see if we can spot any hidden bottlenecks.
CipherShade CipherShade
Sounds like a solid line of attack. I’m leaning on a Merkle‑style commitment for the base, but the challenge is the amplification layer—every extra copy adds a collision vector, so I pad the domain and inject a fresh seed per instance. As for the simulator, I’m sliding a trapdoor into the lattice generator; that keeps the proof size linear while the simulator runs in essentially the same time as the honest prover, but it does hinge on the hardness of the SIS instance in a quantum‑aware setting. Think of it as a side‑channel that’s deliberately obfuscated. If the hash function’s preimage resistance slips, we lose the whole chain—so the hash choice is the real bottleneck. We’ll need to keep an eye on the entropy budget and the zero‑knowledge extractor’s round count. Let's dig deeper into the collision matrix.
Clever Clever
Sounds like you’re tightening the safety net. I’d suggest running a quick Monte‑Carlo on the collision matrix first—just a few thousand random seeds to gauge the real collision probability. If it stays low, we can lean on the trapdoor lattice generator and still keep the simulator snappy. Also, maybe hash the seed together with a per‑instance counter; that gives you a tiny entropy bump without blowing the domain. Once you have the numbers, we can pinpoint where the extractor might need more rounds. Let’s crunch those stats and see if the theory holds up under simulation.
CipherShade CipherShade
Got it. Running the Monte‑Carlo on the collision matrix is the cleanest sanity check. I’ll throw a few thousand seeds through the hash‑tree and the lattice generator, collect the hit rate, and feed the data back to the extractor logic. If the numbers stay in the low‑percentile, we’ll tighten the counter‑seed tweak and keep the simulator lean. I’ll ping you once the stats are in; then we can map the round requirements and see where the real bottlenecks sit. Stay tuned.
Clever Clever
Sounds good, keep me posted on those numbers. I’ll be ready to tweak the extractor when you hand over the stats. Looking forward to the next round of insights.