Trait Dpf

pub trait Dpf<const IN_BLEN: usize, const OUT_BLEN: usize, G>
where
    G: Group<OUT_BLEN>,
{
    // Required methods
    fn gen(
        &self,
        f: &PointFn<IN_BLEN, OUT_BLEN, G>,
        s0s: [&[u8; OUT_BLEN]; 2],
    ) -> Share<OUT_BLEN, G>;
    fn eval(
        &self,
        b: bool,
        k: &Share<OUT_BLEN, G>,
        xs: &[&[u8; IN_BLEN]],
        ys: &mut [&mut G],
    );
    fn full_eval(&self, b: bool, k: &Share<OUT_BLEN, G>, ys: &mut [&mut G]);
}

API of distributed point functions (DPFs).

PointFn used here means $f(x) = \beta$ iff. $x = \alpha$, otherwise $f(x) = 0$.

• See PointFn for IN_BLEN and OUT_BLEN.
• See DpfImpl for the implementation.

Required Methods

fn gen( &self, f: &PointFn<IN_BLEN, OUT_BLEN, G>, s0s: [&[u8; OUT_BLEN]; 2], ) -> Share<OUT_BLEN, G>

s0s is $s^{(0)}_0$ and $s^{(0)}_1$ which should be randomly sampled.

fn eval( &self, b: bool, k: &Share<OUT_BLEN, G>, xs: &[&[u8; IN_BLEN]], ys: &mut [&mut G], )

b is the party. false is 0 and true is 1.

fn full_eval(&self, b: bool, k: &Share<OUT_BLEN, G>, ys: &mut [&mut G])

Full domain eval. See Dpf::eval for b. The corresponding xs to ys is the big endian representation of 0..=u*::MAX.

Implementors

impl<const IN_BLEN: usize, const OUT_BLEN: usize, P, G> Dpf<IN_BLEN, OUT_BLEN, G> for DpfImpl<IN_BLEN, OUT_BLEN, P>

where P: Prg<OUT_BLEN, 1>, G: Group<OUT_BLEN>,