Quadratic residuosity problem

Summary

The quadratic residuosity problem (QRP[1]) in computational number theory is to decide, given integers and , whether is a quadratic residue modulo or not. Here for two unknown primes and , and is among the numbers which are not obviously quadratic non-residues (see below).

The problem was first described by Gauss in his Disquisitiones Arithmeticae in 1801. This problem is believed to be computationally difficult. Several cryptographic methods rely on its hardness, see § Applications.

An efficient algorithm for the quadratic residuosity problem immediately implies efficient algorithms for other number theoretic problems, such as deciding whether a composite of unknown factorization is the product of 2 or 3 primes.[2]

Precise formulation edit

Given integers   and  ,   is said to be a quadratic residue modulo   if there exists an integer   such that

 .

Otherwise we say it is a quadratic non-residue. When   is a prime, it is customary to use the Legendre symbol:

 

This is a multiplicative character which means   for exactly   of the values  , and it is   for the remaining.

It is easy to compute using the law of quadratic reciprocity in a manner akin to the Euclidean algorithm; see Legendre symbol.

Consider now some given   where   and   are two different unknown primes. A given   is a quadratic residue modulo   if and only if   is a quadratic residue modulo both   and   and  .

Since we don't know   or  , we cannot compute   and  . However, it is easy to compute their product. This is known as the Jacobi symbol:

 

This also can be efficiently computed using the law of quadratic reciprocity for Jacobi symbols.

However,   cannot in all cases tell us whether   is a quadratic residue modulo   or not! More precisely, if   then   is necessarily a quadratic non-residue modulo either   or  , in which case we are done. But if   then it is either the case that   is a quadratic residue modulo both   and  , or a quadratic non-residue modulo both   and  . We cannot distinguish these cases from knowing just that  .

This leads to the precise formulation of the quadratic residue problem:

Problem: Given integers   and  , where   and   are distinct unknown primes, and where  , determine whether   is a quadratic residue modulo   or not.

Distribution of residues edit

If   is drawn uniformly at random from integers   such that  , is   more often a quadratic residue or a quadratic non-residue modulo  ?

As mentioned earlier, for exactly half of the choices of  , then  , and for the rest we have  . By extension, this also holds for half the choices of  . Similarly for  . From basic algebra, it follows that this partitions   into 4 parts of equal size, depending on the sign of   and  .

The allowed   in the quadratic residue problem given as above constitute exactly those two parts corresponding to the cases   and  . Consequently, exactly half of the possible   are quadratic residues and the remaining are not.

Applications edit

The intractability of the quadratic residuosity problem is the basis for the security of the Blum Blum Shub pseudorandom number generator. It also yields the public key Goldwasser–Micali cryptosystem,[3][4] as well as the identity based Cocks scheme.

See also edit

References edit

  1. ^ Kaliski, Burt (2011). "Quadratic Residuosity Problem". Encyclopedia of Cryptography and Security. p. 1003. doi:10.1007/978-1-4419-5906-5_429. ISBN 978-1-4419-5905-8.
  2. ^ Adleman, L. (1980). "On Distinguishing Prime Numbers from Composite Numbers". Proceedings of the 21st IEEE Symposium on the Foundations of Computer Science (FOCS), Syracuse, N.Y. pp. 387–408. doi:10.1109/SFCS.1980.28. ISSN 0272-5428.
  3. ^ S. Goldwasser, S. Micali (1982). "Probabilistic encryption & how to play mental poker keeping secret all partial information". Proceedings of the fourteenth annual ACM symposium on Theory of computing - STOC '82. pp. 365–377. doi:10.1145/800070.802212. ISBN 0897910702. S2CID 10316867.
  4. ^ S. Goldwasser, S. Micali (1984). "Probabilistic encryption". Journal of Computer and System Sciences. 28 (2): 270–299. doi:10.1016/0022-0000(84)90070-9.