Latest revision as of 00:24, 20 January 2026

Bias

With respect to the uniform distribution on \([0,n-1]\), the bias is defined to be the maximum value of \(\{probability(S) - (\frac{

Source: FIPS 186-5 | Category:

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	{{CyberTerm\|definition=With respect to the uniform distribution on ~~<span class="math-tex">~~\([0,n-1]\)~~</span>~~, the bias is defined to be the maximum value of ~~<span class="math-tex">~~\(\{probability(S) - (\frac{\|S\|}{n})\}\)~~</span>~~ taken over all subsets ~~<span class="math-tex">~~\(S\)~~</span><em>~~ ~~</em>~~of ~~<span class="math-tex">~~\([0,n-1]\)~~</span>~~. This measures the maximum advantage that an adversary has in predicting any event.\|source=FIPS 186-5}}		{{CyberTerm\|definition=With respect to the uniform distribution on \([0,n-1]\), the bias is defined to be the maximum value of \(\{probability(S) - (\frac{\|S\|}{n})\}\) taken over all subsets \(S\) of \([0,n-1]\). This measures the maximum advantage that an adversary has in predicting any event.\|source=FIPS 186-5}}