Crate w3f_bls

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§Aggregate BLS signature library with extensive tuning options.

In short, anyone using BLS signatures should normally choose both an orientation as well as some aggregation and batching strategies These two decissions impact performance dramaticaly, but making the optimal choises requires some attentiom. This crate employs convenient abstraction boundaries between curver arithmatic, verifier routines, and aggregated and/or batched BLS signatures.

§Pairings

If we have two elliptic curve with a pairing e, then a BLS signature sigma = s*H(msg) by a public key S = s g1 can be verified with the one equation e(g1,sigma) = e(S,H(msg)). These simple BLS signatures are very slow to verify however because the pairing map e is far slower than many cryptographic primitives.

Our pairing e maps from a small curve over F(q) and a larger curve over F(q^2) into some multipliccative group if a field, normally over F(q^12). In principle, this map e into F(q^12) makes pairing based cryptography like BLS less secure than other elliptic curve based cryptography, which further slows down BLS signatures by requiring larger q.

§Arithmatic

An almost universally applicable otimization is to seperate the “Miller loop” that computes in F(q) and F(q^2) from the slow final exponentiation that happens in F(q^12). So our actual verification equation more resembles e(-g1,sigma) e(S,H(msg)) = 1.

As one curve is smaller and hence faster, the user should choose which orientation of curves they prefer, meaning to which curve they hash, and which curves hold the signatues and public keys. In other words, your desired aggregation techniques and usage characteristics should determine if youp refer the verification equation e(g1,sigma) = e(S,H(msg)) or the fliped form e(sigma,g2) = e(H(msg),S). See UsualBLS and TinyBLS.

§Aggregation

We consder BLS signatures interesting because they support dramatic optimizations when handling multiple signatures together. In fact, BLS signatures support aggregation by a third party that makes signatures smaller, not merely batch verification.
All this stems from the bilinearity of e, meaning we reduce the number of pairings, or size of the miller loop, by appling rules like e(x,z)e(y,z) = e(x+y,z), e(x,y)e(x,z) = e(x,y+z), etc.

In essence, our aggregation tricks fall into two categories, linear aggregation, in which only addition is used, and delinearized optimiztions, in which we multiply curve points by values unforseeable to the signers. In general, linear techniques provide much better performance, but require stronger invariants be maintained by the caller, like messages being distinct, or limited signer sets with proofs-of-possession. Also, the delinearized techniques remain secure without tricky assumptions, but require more computation.

§Verification

We can often further reduce the pairings required in the verification equation, beyond the naieve information tracked by the aggregated signature itself. Aggregated signature must state all the individual messages and/or public keys, but verifiers may collapse anything permitted. We thus encounter aggregation-like decissions that impact verifier performance.

We therefore provide an abstract interface that permits doing further aggregation and/or passing any aggregate signature to any verification routine.

As a rule, we also attempt to batch normalize different arithmatic outputs, but concievably small signer set sizes might make this a pessimization.

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  • Internal message hash type. Short for frequent rehashing by HashMap, etc.

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