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In mathematics and computer science, a balanced Boolean function is a Boolean function whose output yields as many 0s as 1s over its input set. This means that for a uniformly random input string of bits, the probability of getting a 1 is 1/2.[1]

Examples

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Examples of balanced Boolean functions are the majority function,[1] the "dictatorship function" that copies the first bit of its input to the output,[1] and the parity check function that produces the exclusive or of the input bits.[2]

If is a bent function on bits, and is any nonzero vector of bits, then the function that maps to is balanced. The bent functions are exactly the functions for which this is true, for all nonzero choices of .[3]

The dictatorship function can be evaluated after examining only a single bit of the input, but that bit must always be examined. Benjamini, Schramm, and Wilson describe a more complex example based on percolation theory with the property that a randomized Las Vegas algorithm can compute the function exactly while ensuring that the probability of reading any particular input bit is small, roughly inversely proportional to the square root of the number of bits.[1]

Application

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Balanced Boolean functions are used in cryptography, where being balanced is one of "the most important criteria for cryptographically strong Boolean functions".[3] If a function is not balanced, it will have a statistical bias, making it subject to cryptanalysis such as the correlation attack.

References

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  1. ^ a b c d Benjamini, Itai; Schramm, Oded; Wilson, David Bruce (2005), "Balanced boolean functions that can be evaluated so that every input bit is unlikely to be read", in Gabow, Harold N.; Fagin, Ronald (eds.), Proceedings of the 37th Annual ACM Symposium on Theory of Computing, Baltimore, MD, USA, May 22–24, 2005, Association for Computing Machinery, pp. 244–250, arXiv:math.PR/0410282, doi:10.1145/1060590.1060627, ISBN 1-58113-960-8
  2. ^ Chakrabarty, K.; Hayes, J.P. (1998), "Balanced Boolean functions", IEE Proceedings - Computers and Digital Techniques, 145 (1): 52, doi:10.1049/ip-cdt:19981769 (inactive 11 July 2025){{citation}}: CS1 maint: DOI inactive as of July 2025 (link)
  3. ^ a b Seberry, Jennifer; Zhang, Xian-Mo; Zheng, Yuliang (1993), "Nonlinearly balanced Boolean functions and their propagation characteristics", in Stinson, Douglas R. (ed.), Advances in Cryptology – CRYPTO '93, 13th Annual International Cryptology Conference, Santa Barbara, California, USA, August 22–26, 1993, Proceedings, Lecture Notes in Computer Science, vol. 773, Springer, pp. 49–60, doi:10.1007/3-540-48329-2_5, ISBN 978-3-540-57766-9

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Boolean function

In mathematics, a Boolean function is a function whose arguments and result assume values from a two-element set (usually {true, false}, {0,1} or {−1,1})

List of Boolean algebra topics

Analysis of Boolean functions Balanced Boolean function Bent function Boolean algebras canonically defined Boolean function Boolean matrix Boolean-valued function

Bent function

output of the function and a linear function is minimal. In addition, the derivatives of a bent function are balanced Boolean functions, so for any change

Weight-balanced tree

be more efficient and highly-parallelizable. Join The function Join is on two weight-balanced trees t1 and t2 and a key k and will return a tree containing

Simon (cipher)

making them available for use by commercial entities. Balanced Boolean function Bent function The Simon and Speck Families Of Lightweight Block Ciphers

Join-based tree algorithms

right child r {\displaystyle r} . The join algorithm for weight-balanced trees: function joinRightWB(TL, k, TR) (l, k', c) := expose(TL) if w(TL) =α w(TR)

Correlation attack

(LFSRs) using a Boolean function. Correlation attacks exploit a statistical weakness that arises from the specific Boolean function chosen for the keystream

Decision table

table is the simplest to describe. The condition alternatives are simple Boolean values, and the action entries are check-marks, representing which of the