Computational indistinguishability

In computational complexity and cryptography, two families of distributions are computationally indistinguishable if no efficient algorithm can tell the difference between them except with negligible probability. == Formal definition == Let { D n } n ∈ N {\displaystyle \scriptstyle \{D_{n}\}_{n\in \mathbb {N} }} and { E n } n ∈ N {\displaystyle \scriptstyle \{E_{n}\}_{n\in \mathbb {N} }} be two distribution ensembles indexed by a security parameter n (which usually refers to the length of the input); we say they are computationally indistinguishable if for any non-uniform probabilistic polynomial time algorithm A, the following quantity is a negligible function in n: δ ( n ) = | Pr x ← D n [ A ( x ) = 1 ] − Pr x ← E n [ A ( x ) = 1 ] | .

Source: Wikipedia — Computational indistinguishability (CC BY-SA 4.0)

Computational indistinguishability

In computational complexity and cryptography, two families of distributions are computationally indistinguishable if no efficient algorithm can tell the difference between them except with negligible probability. == Formal definition == Let { D n } n ∈ N {\displaystyle \scriptstyle \{D_{n}\}_{n\in \mathbb {N} }} and { E n } n ∈ N {\displaystyle \scriptstyle \{E_{n}\}_{n\in \mathbb {N} }} be two distribution ensembles indexed by a security parameter n (which usually refers to the length of the input); we say they are computationally indistinguishable if for any non-uniform probabilistic polynomial time algorithm A, the following quantity is a negligible function in n: δ ( n ) = | Pr x ← D n [ A ( x ) = 1 ] − Pr x ← E n [ A ( x ) = 1 ] | .

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Source: Wikipedia "Computational indistinguishability" · CC BY-SA 4.0

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