// Copyright (c) 2015-2022 The Decred developers // Copyright 2013-2014 The btcsuite developers // Use of this source code is governed by an ISC // license that can be found in the LICENSE file. package secp256k1 import ( "encoding/hex" "math/bits" ) // References: // [SECG]: Recommended Elliptic Curve Domain Parameters // https://www.secg.org/sec2-v2.pdf // // [GECC]: Guide to Elliptic Curve Cryptography (Hankerson, Menezes, Vanstone) // // [BRID]: On Binary Representations of Integers with Digits -1, 0, 1 // (Prodinger, Helmut) // // [STWS]: Secure-TWS: Authenticating Node to Multi-user Communication in // Shared Sensor Networks (Oliveira, Leonardo B. et al) // All group operations are performed using Jacobian coordinates. For a given // (x, y) position on the curve, the Jacobian coordinates are (x1, y1, z1) // where x = x1/z1^2 and y = y1/z1^3. // hexToFieldVal converts the passed hex string into a FieldVal and will panic // if there is an error. This is only provided for the hard-coded constants so // errors in the source code can be detected. It will only (and must only) be // called with hard-coded values. func hexToFieldVal(s string) *FieldVal { b, err := hex.DecodeString(s) if err != nil { panic("invalid hex in source file: " + s) } var f FieldVal if overflow := f.SetByteSlice(b); overflow { panic("hex in source file overflows mod P: " + s) } return &f } // hexToModNScalar converts the passed hex string into a ModNScalar and will // panic if there is an error. This is only provided for the hard-coded // constants so errors in the source code can be detected. It will only (and // must only) be called with hard-coded values. func hexToModNScalar(s string) *ModNScalar { var isNegative bool if len(s) > 0 && s[0] == '-' { isNegative = true s = s[1:] } if len(s)%2 != 0 { s = "0" + s } b, err := hex.DecodeString(s) if err != nil { panic("invalid hex in source file: " + s) } var scalar ModNScalar if overflow := scalar.SetByteSlice(b); overflow { panic("hex in source file overflows mod N scalar: " + s) } if isNegative { scalar.Negate() } return &scalar } var ( // The following constants are used to accelerate scalar point // multiplication through the use of the endomorphism: // // φ(Q) ⟼ λ*Q = (β*Q.x mod p, Q.y) // // See the code in the deriveEndomorphismParams function in genprecomps.go // for details on their derivation. // // Additionally, see the scalar multiplication function in this file for // details on how they are used. endoNegLambda = hexToModNScalar("-5363ad4cc05c30e0a5261c028812645a122e22ea20816678df02967c1b23bd72") endoBeta = hexToFieldVal("7ae96a2b657c07106e64479eac3434e99cf0497512f58995c1396c28719501ee") endoNegB1 = hexToModNScalar("e4437ed6010e88286f547fa90abfe4c3") endoNegB2 = hexToModNScalar("-3086d221a7d46bcde86c90e49284eb15") endoZ1 = hexToModNScalar("3086d221a7d46bcde86c90e49284eb153daa8a1471e8ca7f") endoZ2 = hexToModNScalar("e4437ed6010e88286f547fa90abfe4c4221208ac9df506c6") // Alternatively, the following parameters are valid as well, however, // benchmarks show them to be about 2% slower in practice. // endoNegLambda = hexToModNScalar("-ac9c52b33fa3cf1f5ad9e3fd77ed9ba4a880b9fc8ec739c2e0cfc810b51283ce") // endoBeta = hexToFieldVal("851695d49a83f8ef919bb86153cbcb16630fb68aed0a766a3ec693d68e6afa40") // endoNegB1 = hexToModNScalar("3086d221a7d46bcde86c90e49284eb15") // endoNegB2 = hexToModNScalar("-114ca50f7a8e2f3f657c1108d9d44cfd8") // endoZ1 = hexToModNScalar("114ca50f7a8e2f3f657c1108d9d44cfd95fbc92c10fddd145") // endoZ2 = hexToModNScalar("3086d221a7d46bcde86c90e49284eb153daa8a1471e8ca7f") ) // JacobianPoint is an element of the group formed by the secp256k1 curve in // Jacobian projective coordinates and thus represents a point on the curve. type JacobianPoint struct { // The X coordinate in Jacobian projective coordinates. The affine point is // X/z^2. X FieldVal // The Y coordinate in Jacobian projective coordinates. The affine point is // Y/z^3. Y FieldVal // The Z coordinate in Jacobian projective coordinates. Z FieldVal } // MakeJacobianPoint returns a Jacobian point with the provided X, Y, and Z // coordinates. func MakeJacobianPoint(x, y, z *FieldVal) JacobianPoint { var p JacobianPoint p.X.Set(x) p.Y.Set(y) p.Z.Set(z) return p } // Set sets the Jacobian point to the provided point. func (p *JacobianPoint) Set(other *JacobianPoint) { p.X.Set(&other.X) p.Y.Set(&other.Y) p.Z.Set(&other.Z) } // ToAffine reduces the Z value of the existing point to 1 effectively // making it an affine coordinate in constant time. The point will be // normalized. func (p *JacobianPoint) ToAffine() { // Inversions are expensive and both point addition and point doubling // are faster when working with points that have a z value of one. So, // if the point needs to be converted to affine, go ahead and normalize // the point itself at the same time as the calculation is the same. var zInv, tempZ FieldVal zInv.Set(&p.Z).Inverse() // zInv = Z^-1 tempZ.SquareVal(&zInv) // tempZ = Z^-2 p.X.Mul(&tempZ) // X = X/Z^2 (mag: 1) p.Y.Mul(tempZ.Mul(&zInv)) // Y = Y/Z^3 (mag: 1) p.Z.SetInt(1) // Z = 1 (mag: 1) // Normalize the x and y values. p.X.Normalize() p.Y.Normalize() } // addZ1AndZ2EqualsOne adds two Jacobian points that are already known to have // z values of 1 and stores the result in the provided result param. That is to // say result = p1 + p2. It performs faster addition than the generic add // routine since less arithmetic is needed due to the ability to avoid the z // value multiplications. // // NOTE: The points must be normalized for this function to return the correct // result. The resulting point will be normalized. func addZ1AndZ2EqualsOne(p1, p2, result *JacobianPoint) { // To compute the point addition efficiently, this implementation splits // the equation into intermediate elements which are used to minimize // the number of field multiplications using the method shown at: // https://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#addition-mmadd-2007-bl // // In particular it performs the calculations using the following: // H = X2-X1, HH = H^2, I = 4*HH, J = H*I, r = 2*(Y2-Y1), V = X1*I // X3 = r^2-J-2*V, Y3 = r*(V-X3)-2*Y1*J, Z3 = 2*H // // This results in a cost of 4 field multiplications, 2 field squarings, // 6 field additions, and 5 integer multiplications. x1, y1 := &p1.X, &p1.Y x2, y2 := &p2.X, &p2.Y x3, y3, z3 := &result.X, &result.Y, &result.Z // When the x coordinates are the same for two points on the curve, the // y coordinates either must be the same, in which case it is point // doubling, or they are opposite and the result is the point at // infinity per the group law for elliptic curve cryptography. if x1.Equals(x2) { if y1.Equals(y2) { // Since x1 == x2 and y1 == y2, point doubling must be // done, otherwise the addition would end up dividing // by zero. DoubleNonConst(p1, result) return } // Since x1 == x2 and y1 == -y2, the sum is the point at // infinity per the group law. x3.SetInt(0) y3.SetInt(0) z3.SetInt(0) return } // Calculate X3, Y3, and Z3 according to the intermediate elements // breakdown above. var h, i, j, r, v FieldVal var negJ, neg2V, negX3 FieldVal h.Set(x1).Negate(1).Add(x2) // H = X2-X1 (mag: 3) i.SquareVal(&h).MulInt(4) // I = 4*H^2 (mag: 4) j.Mul2(&h, &i) // J = H*I (mag: 1) r.Set(y1).Negate(1).Add(y2).MulInt(2) // r = 2*(Y2-Y1) (mag: 6) v.Mul2(x1, &i) // V = X1*I (mag: 1) negJ.Set(&j).Negate(1) // negJ = -J (mag: 2) neg2V.Set(&v).MulInt(2).Negate(2) // neg2V = -(2*V) (mag: 3) x3.Set(&r).Square().Add(&negJ).Add(&neg2V) // X3 = r^2-J-2*V (mag: 6) negX3.Set(x3).Negate(6) // negX3 = -X3 (mag: 7) j.Mul(y1).MulInt(2).Negate(2) // J = -(2*Y1*J) (mag: 3) y3.Set(&v).Add(&negX3).Mul(&r).Add(&j) // Y3 = r*(V-X3)-2*Y1*J (mag: 4) z3.Set(&h).MulInt(2) // Z3 = 2*H (mag: 6) // Normalize the resulting field values as needed. x3.Normalize() y3.Normalize() z3.Normalize() } // addZ1EqualsZ2 adds two Jacobian points that are already known to have the // same z value and stores the result in the provided result param. That is to // say result = p1 + p2. It performs faster addition than the generic add // routine since less arithmetic is needed due to the known equivalence. // // NOTE: The points must be normalized for this function to return the correct // result. The resulting point will be normalized. func addZ1EqualsZ2(p1, p2, result *JacobianPoint) { // To compute the point addition efficiently, this implementation splits // the equation into intermediate elements which are used to minimize // the number of field multiplications using a slightly modified version // of the method shown at: // https://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#addition-zadd-2007-m // // In particular it performs the calculations using the following: // A = X2-X1, B = A^2, C=Y2-Y1, D = C^2, E = X1*B, F = X2*B // X3 = D-E-F, Y3 = C*(E-X3)-Y1*(F-E), Z3 = Z1*A // // This results in a cost of 5 field multiplications, 2 field squarings, // 9 field additions, and 0 integer multiplications. x1, y1, z1 := &p1.X, &p1.Y, &p1.Z x2, y2 := &p2.X, &p2.Y x3, y3, z3 := &result.X, &result.Y, &result.Z // When the x coordinates are the same for two points on the curve, the // y coordinates either must be the same, in which case it is point // doubling, or they are opposite and the result is the point at // infinity per the group law for elliptic curve cryptography. if x1.Equals(x2) { if y1.Equals(y2) { // Since x1 == x2 and y1 == y2, point doubling must be // done, otherwise the addition would end up dividing // by zero. DoubleNonConst(p1, result) return } // Since x1 == x2 and y1 == -y2, the sum is the point at // infinity per the group law. x3.SetInt(0) y3.SetInt(0) z3.SetInt(0) return } // Calculate X3, Y3, and Z3 according to the intermediate elements // breakdown above. var a, b, c, d, e, f FieldVal var negX1, negY1, negE, negX3 FieldVal negX1.Set(x1).Negate(1) // negX1 = -X1 (mag: 2) negY1.Set(y1).Negate(1) // negY1 = -Y1 (mag: 2) a.Set(&negX1).Add(x2) // A = X2-X1 (mag: 3) b.SquareVal(&a) // B = A^2 (mag: 1) c.Set(&negY1).Add(y2) // C = Y2-Y1 (mag: 3) d.SquareVal(&c) // D = C^2 (mag: 1) e.Mul2(x1, &b) // E = X1*B (mag: 1) negE.Set(&e).Negate(1) // negE = -E (mag: 2) f.Mul2(x2, &b) // F = X2*B (mag: 1) x3.Add2(&e, &f).Negate(2).Add(&d) // X3 = D-E-F (mag: 4) negX3.Set(x3).Negate(4) // negX3 = -X3 (mag: 5) y3.Set(y1).Mul(f.Add(&negE)).Negate(1) // Y3 = -(Y1*(F-E)) (mag: 2) y3.Add(e.Add(&negX3).Mul(&c)) // Y3 = C*(E-X3)+Y3 (mag: 3) z3.Mul2(z1, &a) // Z3 = Z1*A (mag: 1) // Normalize the resulting field values as needed. x3.Normalize() y3.Normalize() z3.Normalize() } // addZ2EqualsOne adds two Jacobian points when the second point is already // known to have a z value of 1 (and the z value for the first point is not 1) // and stores the result in the provided result param. That is to say result = // p1 + p2. It performs faster addition than the generic add routine since // less arithmetic is needed due to the ability to avoid multiplications by the // second point's z value. // // NOTE: The points must be normalized for this function to return the correct // result. The resulting point will be normalized. func addZ2EqualsOne(p1, p2, result *JacobianPoint) { // To compute the point addition efficiently, this implementation splits // the equation into intermediate elements which are used to minimize // the number of field multiplications using the method shown at: // https://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#addition-madd-2007-bl // // In particular it performs the calculations using the following: // Z1Z1 = Z1^2, U2 = X2*Z1Z1, S2 = Y2*Z1*Z1Z1, H = U2-X1, HH = H^2, // I = 4*HH, J = H*I, r = 2*(S2-Y1), V = X1*I // X3 = r^2-J-2*V, Y3 = r*(V-X3)-2*Y1*J, Z3 = (Z1+H)^2-Z1Z1-HH // // This results in a cost of 7 field multiplications, 4 field squarings, // 9 field additions, and 4 integer multiplications. x1, y1, z1 := &p1.X, &p1.Y, &p1.Z x2, y2 := &p2.X, &p2.Y x3, y3, z3 := &result.X, &result.Y, &result.Z // When the x coordinates are the same for two points on the curve, the // y coordinates either must be the same, in which case it is point // doubling, or they are opposite and the result is the point at // infinity per the group law for elliptic curve cryptography. Since // any number of Jacobian coordinates can represent the same affine // point, the x and y values need to be converted to like terms. Due to // the assumption made for this function that the second point has a z // value of 1 (z2=1), the first point is already "converted". var z1z1, u2, s2 FieldVal z1z1.SquareVal(z1) // Z1Z1 = Z1^2 (mag: 1) u2.Set(x2).Mul(&z1z1).Normalize() // U2 = X2*Z1Z1 (mag: 1) s2.Set(y2).Mul(&z1z1).Mul(z1).Normalize() // S2 = Y2*Z1*Z1Z1 (mag: 1) if x1.Equals(&u2) { if y1.Equals(&s2) { // Since x1 == x2 and y1 == y2, point doubling must be // done, otherwise the addition would end up dividing // by zero. DoubleNonConst(p1, result) return } // Since x1 == x2 and y1 == -y2, the sum is the point at // infinity per the group law. x3.SetInt(0) y3.SetInt(0) z3.SetInt(0) return } // Calculate X3, Y3, and Z3 according to the intermediate elements // breakdown above. var h, hh, i, j, r, rr, v FieldVal var negX1, negY1, negX3 FieldVal negX1.Set(x1).Negate(1) // negX1 = -X1 (mag: 2) h.Add2(&u2, &negX1) // H = U2-X1 (mag: 3) hh.SquareVal(&h) // HH = H^2 (mag: 1) i.Set(&hh).MulInt(4) // I = 4 * HH (mag: 4) j.Mul2(&h, &i) // J = H*I (mag: 1) negY1.Set(y1).Negate(1) // negY1 = -Y1 (mag: 2) r.Set(&s2).Add(&negY1).MulInt(2) // r = 2*(S2-Y1) (mag: 6) rr.SquareVal(&r) // rr = r^2 (mag: 1) v.Mul2(x1, &i) // V = X1*I (mag: 1) x3.Set(&v).MulInt(2).Add(&j).Negate(3) // X3 = -(J+2*V) (mag: 4) x3.Add(&rr) // X3 = r^2+X3 (mag: 5) negX3.Set(x3).Negate(5) // negX3 = -X3 (mag: 6) y3.Set(y1).Mul(&j).MulInt(2).Negate(2) // Y3 = -(2*Y1*J) (mag: 3) y3.Add(v.Add(&negX3).Mul(&r)) // Y3 = r*(V-X3)+Y3 (mag: 4) z3.Add2(z1, &h).Square() // Z3 = (Z1+H)^2 (mag: 1) z3.Add(z1z1.Add(&hh).Negate(2)) // Z3 = Z3-(Z1Z1+HH) (mag: 4) // Normalize the resulting field values as needed. x3.Normalize() y3.Normalize() z3.Normalize() } // addGeneric adds two Jacobian points without any assumptions about the z // values of the two points and stores the result in the provided result param. // That is to say result = p1 + p2. It is the slowest of the add routines due // to requiring the most arithmetic. // // NOTE: The points must be normalized for this function to return the correct // result. The resulting point will be normalized. func addGeneric(p1, p2, result *JacobianPoint) { // To compute the point addition efficiently, this implementation splits // the equation into intermediate elements which are used to minimize // the number of field multiplications using the method shown at: // https://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#addition-add-2007-bl // // In particular it performs the calculations using the following: // Z1Z1 = Z1^2, Z2Z2 = Z2^2, U1 = X1*Z2Z2, U2 = X2*Z1Z1, S1 = Y1*Z2*Z2Z2 // S2 = Y2*Z1*Z1Z1, H = U2-U1, I = (2*H)^2, J = H*I, r = 2*(S2-S1) // V = U1*I // X3 = r^2-J-2*V, Y3 = r*(V-X3)-2*S1*J, Z3 = ((Z1+Z2)^2-Z1Z1-Z2Z2)*H // // This results in a cost of 11 field multiplications, 5 field squarings, // 9 field additions, and 4 integer multiplications. x1, y1, z1 := &p1.X, &p1.Y, &p1.Z x2, y2, z2 := &p2.X, &p2.Y, &p2.Z x3, y3, z3 := &result.X, &result.Y, &result.Z // When the x coordinates are the same for two points on the curve, the // y coordinates either must be the same, in which case it is point // doubling, or they are opposite and the result is the point at // infinity. Since any number of Jacobian coordinates can represent the // same affine point, the x and y values need to be converted to like // terms. var z1z1, z2z2, u1, u2, s1, s2 FieldVal z1z1.SquareVal(z1) // Z1Z1 = Z1^2 (mag: 1) z2z2.SquareVal(z2) // Z2Z2 = Z2^2 (mag: 1) u1.Set(x1).Mul(&z2z2).Normalize() // U1 = X1*Z2Z2 (mag: 1) u2.Set(x2).Mul(&z1z1).Normalize() // U2 = X2*Z1Z1 (mag: 1) s1.Set(y1).Mul(&z2z2).Mul(z2).Normalize() // S1 = Y1*Z2*Z2Z2 (mag: 1) s2.Set(y2).Mul(&z1z1).Mul(z1).Normalize() // S2 = Y2*Z1*Z1Z1 (mag: 1) if u1.Equals(&u2) { if s1.Equals(&s2) { // Since x1 == x2 and y1 == y2, point doubling must be // done, otherwise the addition would end up dividing // by zero. DoubleNonConst(p1, result) return } // Since x1 == x2 and y1 == -y2, the sum is the point at // infinity per the group law. x3.SetInt(0) y3.SetInt(0) z3.SetInt(0) return } // Calculate X3, Y3, and Z3 according to the intermediate elements // breakdown above. var h, i, j, r, rr, v FieldVal var negU1, negS1, negX3 FieldVal negU1.Set(&u1).Negate(1) // negU1 = -U1 (mag: 2) h.Add2(&u2, &negU1) // H = U2-U1 (mag: 3) i.Set(&h).MulInt(2).Square() // I = (2*H)^2 (mag: 1) j.Mul2(&h, &i) // J = H*I (mag: 1) negS1.Set(&s1).Negate(1) // negS1 = -S1 (mag: 2) r.Set(&s2).Add(&negS1).MulInt(2) // r = 2*(S2-S1) (mag: 6) rr.SquareVal(&r) // rr = r^2 (mag: 1) v.Mul2(&u1, &i) // V = U1*I (mag: 1) x3.Set(&v).MulInt(2).Add(&j).Negate(3) // X3 = -(J+2*V) (mag: 4) x3.Add(&rr) // X3 = r^2+X3 (mag: 5) negX3.Set(x3).Negate(5) // negX3 = -X3 (mag: 6) y3.Mul2(&s1, &j).MulInt(2).Negate(2) // Y3 = -(2*S1*J) (mag: 3) y3.Add(v.Add(&negX3).Mul(&r)) // Y3 = r*(V-X3)+Y3 (mag: 4) z3.Add2(z1, z2).Square() // Z3 = (Z1+Z2)^2 (mag: 1) z3.Add(z1z1.Add(&z2z2).Negate(2)) // Z3 = Z3-(Z1Z1+Z2Z2) (mag: 4) z3.Mul(&h) // Z3 = Z3*H (mag: 1) // Normalize the resulting field values as needed. x3.Normalize() y3.Normalize() z3.Normalize() } // AddNonConst adds the passed Jacobian points together and stores the result in // the provided result param in *non-constant* time. // // NOTE: The points must be normalized for this function to return the correct // result. The resulting point will be normalized. func AddNonConst(p1, p2, result *JacobianPoint) { // The point at infinity is the identity according to the group law for // elliptic curve cryptography. Thus, ∞ + P = P and P + ∞ = P. if (p1.X.IsZero() && p1.Y.IsZero()) || p1.Z.IsZero() { result.Set(p2) return } if (p2.X.IsZero() && p2.Y.IsZero()) || p2.Z.IsZero() { result.Set(p1) return } // Faster point addition can be achieved when certain assumptions are // met. For example, when both points have the same z value, arithmetic // on the z values can be avoided. This section thus checks for these // conditions and calls an appropriate add function which is accelerated // by using those assumptions. isZ1One := p1.Z.IsOne() isZ2One := p2.Z.IsOne() switch { case isZ1One && isZ2One: addZ1AndZ2EqualsOne(p1, p2, result) return case p1.Z.Equals(&p2.Z): addZ1EqualsZ2(p1, p2, result) return case isZ2One: addZ2EqualsOne(p1, p2, result) return } // None of the above assumptions are true, so fall back to generic // point addition. addGeneric(p1, p2, result) } // doubleZ1EqualsOne performs point doubling on the passed Jacobian point when // the point is already known to have a z value of 1 and stores the result in // the provided result param. That is to say result = 2*p. It performs faster // point doubling than the generic routine since less arithmetic is needed due // to the ability to avoid multiplication by the z value. // // NOTE: The resulting point will be normalized. func doubleZ1EqualsOne(p, result *JacobianPoint) { // This function uses the assumptions that z1 is 1, thus the point // doubling formulas reduce to: // // X3 = (3*X1^2)^2 - 8*X1*Y1^2 // Y3 = (3*X1^2)*(4*X1*Y1^2 - X3) - 8*Y1^4 // Z3 = 2*Y1 // // To compute the above efficiently, this implementation splits the // equation into intermediate elements which are used to minimize the // number of field multiplications in favor of field squarings which // are roughly 35% faster than field multiplications with the current // implementation at the time this was written. // // This uses a slightly modified version of the method shown at: // https://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#doubling-mdbl-2007-bl // // In particular it performs the calculations using the following: // A = X1^2, B = Y1^2, C = B^2, D = 2*((X1+B)^2-A-C) // E = 3*A, F = E^2, X3 = F-2*D, Y3 = E*(D-X3)-8*C // Z3 = 2*Y1 // // This results in a cost of 1 field multiplication, 5 field squarings, // 6 field additions, and 5 integer multiplications. x1, y1 := &p.X, &p.Y x3, y3, z3 := &result.X, &result.Y, &result.Z var a, b, c, d, e, f FieldVal z3.Set(y1).MulInt(2) // Z3 = 2*Y1 (mag: 2) a.SquareVal(x1) // A = X1^2 (mag: 1) b.SquareVal(y1) // B = Y1^2 (mag: 1) c.SquareVal(&b) // C = B^2 (mag: 1) b.Add(x1).Square() // B = (X1+B)^2 (mag: 1) d.Set(&a).Add(&c).Negate(2) // D = -(A+C) (mag: 3) d.Add(&b).MulInt(2) // D = 2*(B+D)(mag: 8) e.Set(&a).MulInt(3) // E = 3*A (mag: 3) f.SquareVal(&e) // F = E^2 (mag: 1) x3.Set(&d).MulInt(2).Negate(16) // X3 = -(2*D) (mag: 17) x3.Add(&f) // X3 = F+X3 (mag: 18) f.Set(x3).Negate(18).Add(&d).Normalize() // F = D-X3 (mag: 1) y3.Set(&c).MulInt(8).Negate(8) // Y3 = -(8*C) (mag: 9) y3.Add(f.Mul(&e)) // Y3 = E*F+Y3 (mag: 10) // Normalize the resulting field values as needed. x3.Normalize() y3.Normalize() z3.Normalize() } // doubleGeneric performs point doubling on the passed Jacobian point without // any assumptions about the z value and stores the result in the provided // result param. That is to say result = 2*p. It is the slowest of the point // doubling routines due to requiring the most arithmetic. // // NOTE: The resulting point will be normalized. func doubleGeneric(p, result *JacobianPoint) { // Point doubling formula for Jacobian coordinates for the secp256k1 // curve: // // X3 = (3*X1^2)^2 - 8*X1*Y1^2 // Y3 = (3*X1^2)*(4*X1*Y1^2 - X3) - 8*Y1^4 // Z3 = 2*Y1*Z1 // // To compute the above efficiently, this implementation splits the // equation into intermediate elements which are used to minimize the // number of field multiplications in favor of field squarings which // are roughly 35% faster than field multiplications with the current // implementation at the time this was written. // // This uses a slightly modified version of the method shown at: // https://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#doubling-dbl-2009-l // // In particular it performs the calculations using the following: // A = X1^2, B = Y1^2, C = B^2, D = 2*((X1+B)^2-A-C) // E = 3*A, F = E^2, X3 = F-2*D, Y3 = E*(D-X3)-8*C // Z3 = 2*Y1*Z1 // // This results in a cost of 1 field multiplication, 5 field squarings, // 6 field additions, and 5 integer multiplications. x1, y1, z1 := &p.X, &p.Y, &p.Z x3, y3, z3 := &result.X, &result.Y, &result.Z var a, b, c, d, e, f FieldVal z3.Mul2(y1, z1).MulInt(2) // Z3 = 2*Y1*Z1 (mag: 2) a.SquareVal(x1) // A = X1^2 (mag: 1) b.SquareVal(y1) // B = Y1^2 (mag: 1) c.SquareVal(&b) // C = B^2 (mag: 1) b.Add(x1).Square() // B = (X1+B)^2 (mag: 1) d.Set(&a).Add(&c).Negate(2) // D = -(A+C) (mag: 3) d.Add(&b).MulInt(2) // D = 2*(B+D)(mag: 8) e.Set(&a).MulInt(3) // E = 3*A (mag: 3) f.SquareVal(&e) // F = E^2 (mag: 1) x3.Set(&d).MulInt(2).Negate(16) // X3 = -(2*D) (mag: 17) x3.Add(&f) // X3 = F+X3 (mag: 18) f.Set(x3).Negate(18).Add(&d).Normalize() // F = D-X3 (mag: 1) y3.Set(&c).MulInt(8).Negate(8) // Y3 = -(8*C) (mag: 9) y3.Add(f.Mul(&e)) // Y3 = E*F+Y3 (mag: 10) // Normalize the resulting field values as needed. x3.Normalize() y3.Normalize() z3.Normalize() } // DoubleNonConst doubles the passed Jacobian point and stores the result in the // provided result parameter in *non-constant* time. // // NOTE: The point must be normalized for this function to return the correct // result. The resulting point will be normalized. func DoubleNonConst(p, result *JacobianPoint) { // Doubling the point at infinity is still infinity. if p.Y.IsZero() || p.Z.IsZero() { result.X.SetInt(0) result.Y.SetInt(0) result.Z.SetInt(0) return } // Slightly faster point doubling can be achieved when the z value is 1 // by avoiding the multiplication on the z value. This section calls // a point doubling function which is accelerated by using that // assumption when possible. if p.Z.IsOne() { doubleZ1EqualsOne(p, result) return } // Fall back to generic point doubling which works with arbitrary z // values. doubleGeneric(p, result) } // mulAdd64 multiplies the two passed base 2^64 digits together, adds the given // value to the result, and returns the 128-bit result via a (hi, lo) tuple // where the upper half of the bits are returned in hi and the lower half in lo. func mulAdd64(digit1, digit2, m uint64) (hi, lo uint64) { // Note the carry on the final add is safe to discard because the maximum // possible value is: // (2^64 - 1)(2^64 - 1) + (2^64 - 1) = 2^128 - 2^64 // and: // 2^128 - 2^64 < 2^128. var c uint64 hi, lo = bits.Mul64(digit1, digit2) lo, c = bits.Add64(lo, m, 0) hi, _ = bits.Add64(hi, 0, c) return hi, lo } // mulAdd64Carry multiplies the two passed base 2^64 digits together, adds both // the given value and carry to the result, and returns the 128-bit result via a // (hi, lo) tuple where the upper half of the bits are returned in hi and the // lower half in lo. func mulAdd64Carry(digit1, digit2, m, c uint64) (hi, lo uint64) { // Note the carry on the high order add is safe to discard because the // maximum possible value is: // (2^64 - 1)(2^64 - 1) + 2*(2^64 - 1) = 2^128 - 1 // and: // 2^128 - 1 < 2^128. var c2 uint64 hi, lo = mulAdd64(digit1, digit2, m) lo, c2 = bits.Add64(lo, c, 0) hi, _ = bits.Add64(hi, 0, c2) return hi, lo } // mul512Rsh320Round computes the full 512-bit product of the two given scalars, // right shifts the result by 320 bits, rounds to the nearest integer, and // returns the result in constant time. // // Note that despite the inputs and output being mod n scalars, the 512-bit // product is NOT reduced mod N prior to the right shift. This is intentional // because it is used for replacing division with multiplication and thus the // intermediate results must be done via a field extension to a larger field. func mul512Rsh320Round(n1, n2 *ModNScalar) ModNScalar { // Convert n1 and n2 to base 2^64 digits. n1Digit0 := uint64(n1.n[0]) | uint64(n1.n[1])<<32 n1Digit1 := uint64(n1.n[2]) | uint64(n1.n[3])<<32 n1Digit2 := uint64(n1.n[4]) | uint64(n1.n[5])<<32 n1Digit3 := uint64(n1.n[6]) | uint64(n1.n[7])<<32 n2Digit0 := uint64(n2.n[0]) | uint64(n2.n[1])<<32 n2Digit1 := uint64(n2.n[2]) | uint64(n2.n[3])<<32 n2Digit2 := uint64(n2.n[4]) | uint64(n2.n[5])<<32 n2Digit3 := uint64(n2.n[6]) | uint64(n2.n[7])<<32 // Compute the full 512-bit product n1*n2. var r0, r1, r2, r3, r4, r5, r6, r7, c uint64 // Terms resulting from the product of the first digit of the second number // by all digits of the first number. // // Note that r0 is ignored because it is not needed to compute the higher // terms and it is shifted out below anyway. c, _ = bits.Mul64(n2Digit0, n1Digit0) c, r1 = mulAdd64(n2Digit0, n1Digit1, c) c, r2 = mulAdd64(n2Digit0, n1Digit2, c) r4, r3 = mulAdd64(n2Digit0, n1Digit3, c) // Terms resulting from the product of the second digit of the second number // by all digits of the first number. // // Note that r1 is ignored because it is no longer needed to compute the // higher terms and it is shifted out below anyway. c, _ = mulAdd64(n2Digit1, n1Digit0, r1) c, r2 = mulAdd64Carry(n2Digit1, n1Digit1, r2, c) c, r3 = mulAdd64Carry(n2Digit1, n1Digit2, r3, c) r5, r4 = mulAdd64Carry(n2Digit1, n1Digit3, r4, c) // Terms resulting from the product of the third digit of the second number // by all digits of the first number. // // Note that r2 is ignored because it is no longer needed to compute the // higher terms and it is shifted out below anyway. c, _ = mulAdd64(n2Digit2, n1Digit0, r2) c, r3 = mulAdd64Carry(n2Digit2, n1Digit1, r3, c) c, r4 = mulAdd64Carry(n2Digit2, n1Digit2, r4, c) r6, r5 = mulAdd64Carry(n2Digit2, n1Digit3, r5, c) // Terms resulting from the product of the fourth digit of the second number // by all digits of the first number. // // Note that r3 is ignored because it is no longer needed to compute the // higher terms and it is shifted out below anyway. c, _ = mulAdd64(n2Digit3, n1Digit0, r3) c, r4 = mulAdd64Carry(n2Digit3, n1Digit1, r4, c) c, r5 = mulAdd64Carry(n2Digit3, n1Digit2, r5, c) r7, r6 = mulAdd64Carry(n2Digit3, n1Digit3, r6, c) // At this point the upper 256 bits of the full 512-bit product n1*n2 are in // r4..r7 (recall the low order results were discarded as noted above). // // Right shift the result 320 bits. Note that the MSB of r4 determines // whether or not to round because it is the final bit that is shifted out. // // Also, notice that r3..r7 would also ordinarily be set to 0 as well for // the full shift, but that is skipped since they are no longer used as // their values are known to be zero. roundBit := r4 >> 63 r2, r1, r0 = r7, r6, r5 // Conditionally add 1 depending on the round bit in constant time. r0, c = bits.Add64(r0, roundBit, 0) r1, c = bits.Add64(r1, 0, c) r2, r3 = bits.Add64(r2, 0, c) // Finally, convert the result to a mod n scalar. // // No modular reduction is needed because the result is guaranteed to be // less than the group order given the group order is > 2^255 and the // maximum possible value of the result is 2^192. var result ModNScalar result.n[0] = uint32(r0) result.n[1] = uint32(r0 >> 32) result.n[2] = uint32(r1) result.n[3] = uint32(r1 >> 32) result.n[4] = uint32(r2) result.n[5] = uint32(r2 >> 32) result.n[6] = uint32(r3) result.n[7] = uint32(r3 >> 32) return result } // splitK returns two scalars (k1 and k2) that are a balanced length-two // representation of the provided scalar such that k ≡ k1 + k2*λ (mod N), where // N is the secp256k1 group order. func splitK(k *ModNScalar) (ModNScalar, ModNScalar) { // The ultimate goal is to decompose k into two scalars that are around // half the bit length of k such that the following equation is satisfied: // // k1 + k2*λ ≡ k (mod n) // // The strategy used here is based on algorithm 3.74 from [GECC] with a few // modifications to make use of the more efficient mod n scalar type, avoid // some costly long divisions, and minimize the number of calculations. // // Start by defining a function that takes a vector v = ∈ ℤ⨯ℤ: // // f(v) = a + bλ (mod n) // // Then, find two vectors, v1 = , and v2 = in ℤ⨯ℤ such that: // 1) v1 and v2 are linearly independent // 2) f(v1) = f(v2) = 0 // 3) v1 and v2 have small Euclidean norm // // The vectors that satisfy these properties are found via the Euclidean // algorithm and are precomputed since both n and λ are fixed values for the // secp256k1 curve. See genprecomps.go for derivation details. // // Next, consider k as a vector in ℚ⨯ℚ and by linear algebra write: // // = g1*v1 + g2*v2, where g1, g2 ∈ ℚ // // Note that, per above, the components of vector v1 are a1 and b1 while the // components of vector v2 are a2 and b2. Given the vectors v1 and v2 were // generated such that a1*b2 - a2*b1 = n, solving the equation for g1 and g2 // yields: // // g1 = b2*k / n // g2 = -b1*k / n // // Observe: // = g1*v1 + g2*v2 // = (b2*k/n)* + (-b1*k/n)* | substitute // = + <-a2*b1*k/n, -b2*b1*k/n> | scalar mul // = | vector add // = <[a1*b2*k - a2*b1*k]/n, 0> | simplify // = | factor out k // = | substitute // = | simplify // // Now, consider an integer-valued vector v: // // v = c1*v1 + c2*v2, where c1, c2 ∈ ℤ (mod n) // // Since vectors v1 and v2 are linearly independent and were generated such // that f(v1) = f(v2) = 0, all possible scalars c1 and c2 also produce a // vector v such that f(v) = 0. // // In other words, c1 and c2 can be any integers and the resulting // decomposition will still satisfy the required equation. However, since // the goal is to produce a balanced decomposition that provides a // performance advantage by minimizing max(k1, k2), c1 and c2 need to be // integers close to g1 and g2, respectively, so the resulting vector v is // an integer-valued vector that is close to . // // Finally, consider the vector u: // // u = - v // // It follows that f(u) = k and thus the two components of vector u satisfy // the required equation: // // k1 + k2*λ ≡ k (mod n) // // Choosing c1 and c2: // ------------------- // // As mentioned above, c1 and c2 need to be integers close to g1 and g2, // respectively. The algorithm in [GECC] chooses the following values: // // c1 = round(g1) = round(b2*k / n) // c2 = round(g2) = round(-b1*k / n) // // However, as section 3.4.2 of [STWS] notes, the aforementioned approach // requires costly long divisions that can be avoided by precomputing // rounded estimates as follows: // // t = bitlen(n) + 1 // z1 = round(2^t * b2 / n) // z2 = round(2^t * -b1 / n) // // Then, use those precomputed estimates to perform a multiplication by k // along with a floored division by 2^t, which is a simple right shift by t: // // c1 = floor(k * z1 / 2^t) = (k * z1) >> t // c2 = floor(k * z2 / 2^t) = (k * z2) >> t // // Finally, round up if last bit discarded in the right shift by t is set by // adding 1. // // As a further optimization, rather than setting t = bitlen(n) + 1 = 257 as // stated by [STWS], this implementation uses a higher precision estimate of // t = bitlen(n) + 64 = 320 because it allows simplification of the shifts // in the internal calculations that are done via uint64s and also allows // the use of floor in the precomputations. // // Thus, the calculations this implementation uses are: // // z1 = floor(b2<<320 / n) | precomputed // z2 = floor((-b1)<<320) / n) | precomputed // c1 = ((k * z1) >> 320) + (((k * z1) >> 319) & 1) // c2 = ((k * z2) >> 320) + (((k * z2) >> 319) & 1) // // Putting it all together: // ------------------------ // // Calculate the following vectors using the values discussed above: // // v = c1*v1 + c2*v2 // u = - v // // The two components of the resulting vector v are: // va = c1*a1 + c2*a2 // vb = c1*b1 + c2*b2 // // Thus, the two components of the resulting vector u are: // k1 = k - va // k2 = 0 - vb = -vb // // As some final optimizations: // // 1) Note that k1 + k2*λ ≡ k (mod n) means that k1 ≡ k - k2*λ (mod n). // Therefore, the computation of va can be avoided to save two // field multiplications and a field addition. // // 2) Since k1 = k - k2*λ = k + k2*(-λ), an additional field negation is // saved by storing and using the negative version of λ. // // 3) Since k2 = -vb = -(c1*b1 + c2*b2) = c1*(-b1) + c2*(-b2), one more // field negation is saved by storing and using the negative versions of // b1 and b2. // // k2 = c1*(-b1) + c2*(-b2) // k1 = k + k2*(-λ) var k1, k2 ModNScalar c1 := mul512Rsh320Round(k, endoZ1) c2 := mul512Rsh320Round(k, endoZ2) k2.Add2(c1.Mul(endoNegB1), c2.Mul(endoNegB2)) k1.Mul2(&k2, endoNegLambda).Add(k) return k1, k2 } // nafScalar represents a positive integer up to a maximum value of 2^256 - 1 // encoded in non-adjacent form. // // NAF is a signed-digit representation where each digit can be +1, 0, or -1. // // In order to efficiently encode that information, this type uses two arrays, a // "positive" array where set bits represent the +1 signed digits and a // "negative" array where set bits represent the -1 signed digits. 0 is // represented by neither array having a bit set in that position. // // The Pos and Neg methods return the aforementioned positive and negative // arrays, respectively. type nafScalar struct { // pos houses the positive portion of the representation. An additional // byte is required for the positive portion because the NAF encoding can be // up to 1 bit longer than the normal binary encoding of the value. // // neg houses the negative portion of the representation. Even though the // additional byte is not required for the negative portion, since it can // never exceed the length of the normal binary encoding of the value, // keeping the same length for positive and negative portions simplifies // working with the representation and allows extra conditional branches to // be avoided. // // start and end specify the starting and ending index to use within the pos // and neg arrays, respectively. This allows fixed size arrays to be used // versus needing to dynamically allocate space on the heap. // // NOTE: The fields are defined in the order that they are to minimize the // padding on 32-bit and 64-bit platforms. pos [33]byte start, end uint8 neg [33]byte } // Pos returns the bytes of the encoded value with bits set in the positions // that represent a signed digit of +1. func (s *nafScalar) Pos() []byte { return s.pos[s.start:s.end] } // Neg returns the bytes of the encoded value with bits set in the positions // that represent a signed digit of -1. func (s *nafScalar) Neg() []byte { return s.neg[s.start:s.end] } // naf takes a positive integer up to a maximum value of 2^256 - 1 and returns // its non-adjacent form (NAF), which is a unique signed-digit representation // such that no two consecutive digits are nonzero. See the documentation for // the returned type for details on how the representation is encoded // efficiently and how to interpret it // // NAF is useful in that it has the fewest nonzero digits of any signed digit // representation, only 1/3rd of its digits are nonzero on average, and at least // half of the digits will be 0. // // The aforementioned properties are particularly beneficial for optimizing // elliptic curve point multiplication because they effectively minimize the // number of required point additions in exchange for needing to perform a mix // of fewer point additions and subtractions and possibly one additional point // doubling. This is an excellent tradeoff because subtraction of points has // the same computational complexity as addition of points and point doubling is // faster than both. func naf(k []byte) nafScalar { // Strip leading zero bytes. for len(k) > 0 && k[0] == 0x00 { k = k[1:] } // The non-adjacent form (NAF) of a positive integer k is an expression // k = ∑_(i=0, l-1) k_i * 2^i where k_i ∈ {0,±1}, k_(l-1) != 0, and no two // consecutive digits k_i are nonzero. // // The traditional method of computing the NAF of a positive integer is // given by algorithm 3.30 in [GECC]. It consists of repeatedly dividing k // by 2 and choosing the remainder so that the quotient (k−r)/2 is even // which ensures the next NAF digit is 0. This requires log_2(k) steps. // // However, in [BRID], Prodinger notes that a closed form expression for the // NAF representation is the bitwise difference 3k/2 - k/2. This is more // efficient as it can be computed in O(1) versus the O(log(n)) of the // traditional approach. // // The following code makes use of that formula to compute the NAF more // efficiently. // // To understand the logic here, observe that the only way the NAF has a // nonzero digit at a given bit is when either 3k/2 or k/2 has a bit set in // that position, but not both. In other words, the result of a bitwise // xor. This can be seen simply by considering that when the bits are the // same, the subtraction is either 0-0 or 1-1, both of which are 0. // // Further, observe that the "+1" digits in the result are contributed by // 3k/2 while the "-1" digits are from k/2. So, they can be determined by // taking the bitwise and of each respective value with the result of the // xor which identifies which bits are nonzero. // // Using that information, this loops backwards from the least significant // byte to the most significant byte while performing the aforementioned // calculations by propagating the potential carry and high order bit from // the next word during the right shift. kLen := len(k) var result nafScalar var carry uint8 for byteNum := kLen - 1; byteNum >= 0; byteNum-- { // Calculate k/2. Notice the carry from the previous word is added and // the low order bit from the next word is shifted in accordingly. kc := uint16(k[byteNum]) + uint16(carry) var nextWord uint8 if byteNum > 0 { nextWord = k[byteNum-1] } halfK := kc>>1 | uint16(nextWord<<7) // Calculate 3k/2 and determine the non-zero digits in the result. threeHalfK := kc + halfK nonZeroResultDigits := threeHalfK ^ halfK // Determine the signed digits {0, ±1}. result.pos[byteNum+1] = uint8(threeHalfK & nonZeroResultDigits) result.neg[byteNum+1] = uint8(halfK & nonZeroResultDigits) // Propagate the potential carry from the 3k/2 calculation. carry = uint8(threeHalfK >> 8) } result.pos[0] = carry // Set the starting and ending positions within the fixed size arrays to // identify the bytes that are actually used. This is important since the // encoding is big endian and thus trailing zero bytes changes its value. result.start = 1 - carry result.end = uint8(kLen + 1) return result } // ScalarMultNonConst multiplies k*P where k is a scalar modulo the curve order // and P is a point in Jacobian projective coordinates and stores the result in // the provided Jacobian point. // // NOTE: The point must be normalized for this function to return the correct // result. The resulting point will be normalized. func ScalarMultNonConst(k *ModNScalar, point, result *JacobianPoint) { // ------------------------------------------------------------------------- // This makes use of the following efficiently-computable endomorphism to // accelerate the computation: // // φ(P) ⟼ λ*P = (β*P.x mod p, P.y) // // In other words, there is a special scalar λ that every point on the // elliptic curve can be multiplied by that will result in the same point as // performing a single field multiplication of the point's X coordinate by // the special value β. // // This is useful because scalar point multiplication is significantly more // expensive than a single field multiplication given the former involves a // series of point doublings and additions which themselves consist of a // combination of several field multiplications, squarings, and additions. // // So, the idea behind making use of the endomorphism is thus to decompose // the scalar into two scalars that are each about half the bit length of // the original scalar such that: // // k ≡ k1 + k2*λ (mod n) // // This in turn allows the scalar point multiplication to be performed as a // sum of two smaller half-length multiplications as follows: // // k*P = (k1 + k2*λ)*P // = k1*P + k2*λ*P // = k1*P + k2*φ(P) // // Thus, a speedup is achieved so long as it's faster to decompose the // scalar, compute φ(P), and perform a simultaneous multiply of the // half-length point multiplications than it is to compute a full width // point multiplication. // // In practice, benchmarks show the current implementation provides a // speedup of around 30-35% versus not using the endomorphism. // // See section 3.5 in [GECC] for a more rigorous treatment. // ------------------------------------------------------------------------- // Per above, the main equation here to remember is: // k*P = k1*P + k2*φ(P) // // p1 below is P in the equation while p2 is φ(P) in the equation. // // NOTE: φ(x,y) = (β*x,y). The Jacobian z coordinates are the same, so this // math goes through. // // Also, calculate -p1 and -p2 for use in the NAF optimization. p1, p1Neg := new(JacobianPoint), new(JacobianPoint) p1.Set(point) p1Neg.Set(p1) p1Neg.Y.Negate(1).Normalize() p2, p2Neg := new(JacobianPoint), new(JacobianPoint) p2.Set(p1) p2.X.Mul(endoBeta).Normalize() p2Neg.Set(p2) p2Neg.Y.Negate(1).Normalize() // Decompose k into k1 and k2 such that k = k1 + k2*λ (mod n) where k1 and // k2 are around half the bit length of k in order to halve the number of EC // operations. // // Notice that this also flips the sign of the scalars and points as needed // to minimize the bit lengths of the scalars k1 and k2. // // This is done because the scalars are operating modulo the group order // which means that when they would otherwise be a small negative magnitude // they will instead be a large positive magnitude. Since the goal is for // the scalars to have a small magnitude to achieve a performance boost, use // their negation when they are greater than the half order of the group and // flip the positive and negative values of the corresponding point that // will be multiplied by to compensate. // // In other words, transform the calc when k1 is over the half order to: // k1*P = -k1*-P // // Similarly, transform the calc when k2 is over the half order to: // k2*φ(P) = -k2*-φ(P) k1, k2 := splitK(k) if k1.IsOverHalfOrder() { k1.Negate() p1, p1Neg = p1Neg, p1 } if k2.IsOverHalfOrder() { k2.Negate() p2, p2Neg = p2Neg, p2 } // Convert k1 and k2 into their NAF representations since NAF has a lot more // zeros overall on average which minimizes the number of required point // additions in exchange for a mix of fewer point additions and subtractions // at the cost of one additional point doubling. // // This is an excellent tradeoff because subtraction of points has the same // computational complexity as addition of points and point doubling is // faster than both. // // Concretely, on average, 1/2 of all bits will be non-zero with the normal // binary representation whereas only 1/3rd of the bits will be non-zero // with NAF. // // The Pos version of the bytes contain the +1s and the Neg versions contain // the -1s. k1Bytes, k2Bytes := k1.Bytes(), k2.Bytes() k1NAF, k2NAF := naf(k1Bytes[:]), naf(k2Bytes[:]) k1PosNAF, k1NegNAF := k1NAF.Pos(), k1NAF.Neg() k2PosNAF, k2NegNAF := k2NAF.Pos(), k2NAF.Neg() k1Len, k2Len := len(k1PosNAF), len(k2PosNAF) // Add left-to-right using the NAF optimization. See algorithm 3.77 from // [GECC]. // // Point Q = ∞ (point at infinity). var q JacobianPoint m := k1Len if m < k2Len { m = k2Len } for i := 0; i < m; i++ { // Since k1 and k2 are potentially different lengths and the calculation // is being done left to right, pad the front of the shorter one with // 0s. var k1BytePos, k1ByteNeg, k2BytePos, k2ByteNeg byte if i >= m-k1Len { k1BytePos, k1ByteNeg = k1PosNAF[i-(m-k1Len)], k1NegNAF[i-(m-k1Len)] } if i >= m-k2Len { k2BytePos, k2ByteNeg = k2PosNAF[i-(m-k2Len)], k2NegNAF[i-(m-k2Len)] } for mask := uint8(1 << 7); mask > 0; mask >>= 1 { // Q = 2 * Q DoubleNonConst(&q, &q) // Add or subtract the first point based on the signed digit of the // NAF representation of k1 at this bit position. // // +1: Q = Q + p1 // -1: Q = Q - p1 // 0: Q = Q (no change) if k1BytePos&mask == mask { AddNonConst(&q, p1, &q) } else if k1ByteNeg&mask == mask { AddNonConst(&q, p1Neg, &q) } // Add or subtract the second point based on the signed digit of the // NAF representation of k2 at this bit position. // // +1: Q = Q + p2 // -1: Q = Q - p2 // 0: Q = Q (no change) if k2BytePos&mask == mask { AddNonConst(&q, p2, &q) } else if k2ByteNeg&mask == mask { AddNonConst(&q, p2Neg, &q) } } } result.Set(&q) } // ScalarBaseMultNonConst multiplies k*G where k is a scalar modulo the curve // order and G is the base point of the group and stores the result in the // provided Jacobian point. // // NOTE: The resulting point will be normalized. func ScalarBaseMultNonConst(k *ModNScalar, result *JacobianPoint) { bytePoints := s256BytePoints() // Start with the point at infinity. result.X.Zero() result.Y.Zero() result.Z.Zero() // bytePoints has all 256 byte points for each 8-bit window. The strategy // is to add up the byte points. This is best understood by expressing k in // base-256 which it already sort of is. Each "digit" in the 8-bit window // can be looked up using bytePoints and added together. kb := k.Bytes() for i := 0; i < len(kb); i++ { pt := &bytePoints[i][kb[i]] AddNonConst(result, pt, result) } } // isOnCurve returns whether or not the affine point (x,y) is on the curve. func isOnCurve(fx, fy *FieldVal) bool { // Elliptic curve equation for secp256k1 is: y^2 = x^3 + 7 y2 := new(FieldVal).SquareVal(fy).Normalize() result := new(FieldVal).SquareVal(fx).Mul(fx).AddInt(7).Normalize() return y2.Equals(result) } // DecompressY attempts to calculate the Y coordinate for the given X coordinate // such that the result pair is a point on the secp256k1 curve. It adjusts Y // based on the desired oddness and returns whether or not it was successful // since not all X coordinates are valid. // // The magnitude of the provided X coordinate field val must be a max of 8 for a // correct result. The resulting Y field val will have a max magnitude of 2. func DecompressY(x *FieldVal, odd bool, resultY *FieldVal) bool { // The curve equation for secp256k1 is: y^2 = x^3 + 7. Thus // y = +-sqrt(x^3 + 7). // // The x coordinate must be invalid if there is no square root for the // calculated rhs because it means the X coordinate is not for a point on // the curve. x3PlusB := new(FieldVal).SquareVal(x).Mul(x).AddInt(7) if hasSqrt := resultY.SquareRootVal(x3PlusB); !hasSqrt { return false } if resultY.Normalize().IsOdd() != odd { resultY.Negate(1) } return true }