Blum Blum Shub (B.B.S.) is a pseudorandom number generator proposed in 1986 by Lenore Blum, Manuel Blum and Michael Shub that is derived from Michael O. Rabin's one-way function.

Blum Blum Shub takes the form

,

where M = pq is the product of two large primes p and q. At each step of the algorithm, some output is derived from xn+1; the output is commonly either the bit parity of xn+1 or one or more of the least significant bits of xn+1.

The seed x0 should be an integer that is co-prime to M (i.e. p and q are not factors of x0) and not 1 or 0.

The two primes, p and q, should both be congruent to 3 (mod 4) (this guarantees that each quadratic residue has one square root which is also a quadratic residue), and should be safe primes with a small gcd((p-3)/2, (q-3)/2) (this makes the cycle length large).

An interesting characteristic of the Blum Blum Shub generator is the possibility to calculate any xi value directly (via Euler's theorem):

,

where is the Carmichael function. (Here we have ).

Security There is a proof reducing its security to the computational difficulty of factoring. When the primes are chosen appropriately, and O(log log M) lower-order bits of each xn are output, then in the limit as M grows large, distinguishing the output bits from random should be at least as difficult as solving the quadratic residuosity problem modulo M.

The performance of the BBS random-number generator depends on the size of the modulus M and the number of bits per iteration j. While lowering M or increasing j makes the algorithm faster, doing so also reduces the security. A 2005 paper gives concrete, as opposed to asymptotic, security proof of BBS, for a given M and j. The result can also be used to guide choices of the two numbers by balancing expected security against computational cost.

Example Let , and (where is the seed). We can expect to get a large cycle length for those small numbers, because . The generator starts to evaluate by using and creates the sequence , , , = 9, 81, 236, 36, 31, 202. The following table shows the output (in bits) for the different bit selection methods used to determine the output.

Parity bit Least significant bit 0 1 1 0 1 0 1 1 0 0 1 0

The following is a Python implementation that does check for primality.

import sympy

def blum_blum_shub(p1: int, p2: int, seed: int, iterations: int) -> list[int]: """Blum Blum Shub is a pseudorandom number generator.""" assert p1 % 4 == 3 assert p2 % 4 == 3 assert sympy.isprime(p1 // 2) assert sympy.isprime(p2 // 2) n = p1 * p2 numbers = [] for _ in range(iterations): seed = (seed**2) % n if seed in numbers: print(f"The RNG has fallen into a loop at {len(numbers)} steps") return numbers numbers.append(seed) return numbers

print(blum_blum_shub(11, 23, 3, 100))

The following Common Lisp implementation provides a simple demonstration of the generator, in particular regarding the three bit selection methods. The requirements imposed upon the parameters p, q and s (seed) are not checked.

(defun get-number-of-1-bits (bits) "Returns the number of 1-valued bits in the integer-encoded BITS." (declare (type (integer 0 *) bits)) (the (integer 0 *) (logcount bits)))

(defun get-even-parity-bit (bits) "Returns the even parity bit of the integer-encoded BITS." (declare (type (integer 0 *) bits)) (the bit (mod (get-number-of-1-bits bits) 2)))

(defun get-least-significant-bit (bits) "Returns the least significant bit of the integer-encoded BITS." (declare (type (integer 0 *) bits)) (the bit (ldb (byte 1 0) bits)))

(defun make-blum-blum-shub (&key (p 11) (q 23) (s 3)) "Returns a function of no arguments which represents a simple Blum-Blum-Shub pseudorandom number generator, configured to use the generator parameters P, Q, and S (seed), and returning three values: (1) the number x[n+1], (2) the even parity bit of the number, (3) the least significant bit of the number.

Please note that the parameters P, Q, and S are not checked in accordance to the conditions described in the article." (declare (type (integer 0 *) p q s)) (let ((M (* p q)) ;; M = p * q (x[n] s)) ;; x0 = seed (declare (type (integer 0 *) M x[n])) #'(lambda () ;; x[n+1] = x[n]^2 mod M (let ((x[n+1] (mod (* x[n] x[n]) M))) (declare (type (integer 0 *) x[n+1])) ;; Compute the random bit(s) based on x[n+1]. (let ((even-parity-bit (get-even-parity-bit x[n+1])) (least-significant-bit (get-least-significant-bit x[n+1]))) (declare (type bit even-parity-bit)) (declare (type bit least-significant-bit)) ;; Update the state such that x[n+1] becomes the new x[n]. (setf x[n] x[n+1]) (values x[n+1] even-parity-bit least-significant-bit))))))

;; Print the exemplary outputs. (let ((bbs (make-blum-blum-shub :p 11 :q 23 :s 3))) (declare (type (function () (values (integer 0 *) bit bit)) bbs)) (format T "~&Keys: E = even parity, L = least significant") (format T "~2%") (format T "~&x[n+1] | E | L") (format T "~&--------------") (loop repeat 6 do (multiple-value-bind (x[n+1] even-parity-bit least-significant-bit) (funcall bbs) (declare (type (integer 0 *) x[n+1])) (declare (type bit even-parity-bit)) (declare (type bit least-significant-bit)) (format T "~&~6d | ~d | ~d" x[n+1] even-parity-bit least-significant-bit))))

See also Blum–Micali algorithm

References Citations

Sources

External links GMPBBS, a C-language implementation by Mark Rossmiller BlumBlumShub, a Java-language implementation by Mark Rossmiller An implementation in Java Randomness tests