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The Data Authentication Algorithm (DAA) is a former U.S. government standard for producing cryptographic message authentication codes. DAA is defined in FIPS PUB 113, [1] which was withdrawn on September 1, 2008. [citation needed] The algorithm is not considered secure by today's standards.
Direct Anonymous Attestation (DAA) is a cryptographic primitive which enables remote authentication of a trusted computer whilst preserving privacy of the platform's user. The protocol has been adopted by the Trusted Computing Group (TCG) in the latest version of its Trusted Platform Module (TPM) specification [ 1 ] to address privacy concerns ...
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.
Algorithms + Data Structures = Programs [1] is a 1976 book written by Niklaus Wirth covering some of the fundamental topics of system engineering, computer programming, particularly that algorithms and data structures are inherently related. For example, if one has a sorted list one will use a search algorithm optimal for sorted lists.
Many algorithms with bad worst-case performance have good average-case performance. For problems we want to solve, this is a good thing: we can hope that the particular instances we care about are average. For cryptography, this is very bad: we want typical instances of a cryptographic problem to be hard.
Input enhancement when searching has been an essential component of the algorithm world for some time in computer science. The main idea behind this principle is that the efficiency of a search is much faster when the time is taken to create or sort a data structure of the given input before attempting to search for the element in said data structure.
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In analysis of algorithms, probabilistic analysis of algorithms is an approach to estimate the computational complexity of an algorithm or a computational problem. It starts from an assumption about a probabilistic distribution of the set of all possible inputs.