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File verification is the process of using an algorithm for verifying the integrity of a computer file, usually by checksum.This can be done by comparing two files bit-by-bit, but requires two copies of the same file, and may miss systematic corruptions which might occur to both files.
File integrity monitoring (FIM) is an internal control or process that performs the act of validating the integrity of operating system and application software files using a verification method between the current file state and a known, good baseline.
The following tables compare general and technical information for a number of cryptographic hash functions. See the individual functions' articles for further information. This article is not all-inclusive or necessarily up-to-date. An overview of hash function security/cryptanalysis can be found at hash function security summary.
Comparison of implementations of message authentication code (MAC) algorithms. A MAC is a short piece of information used to authenticate a message—in other words, to confirm that the message came from the stated sender (its authenticity) and has not been changed in transit (its integrity).
Calculation and checking of checksums and hashes. File utility operations File shredder for safe file deletion. Splitting or concatenating of files. File compare (only byte by byte) Importing and exporting of hex files (Intel HEX, Motorola S-record) Exporting of data to several formats Source code (C, Pascal, Java, C#, VB.NET, PureBasic)
SHA-256: 256 bits Merkle–Damgård construction: SHA-384: 384 bits Merkle–Damgård construction: SHA-512: 512 bits Merkle–Damgård construction: SHA-3 (subset of Keccak) arbitrary sponge function: Skein: arbitrary Unique Block Iteration: Snefru: 128 or 256 bits hash Spectral Hash: 512 bits wide-pipe Merkle–Damgård construction Streebog ...
Algorithm and variant Output size (bits) Internal state size (bits) Block size (bits) Rounds Operations Security against collision attacks (bits) Security against length extension attacks
The content of such spam may often vary in its details, which would render normal checksumming ineffective. By contrast, a "fuzzy checksum" reduces the body text to its characteristic minimum, then generates a checksum in the usual manner. This greatly increases the chances of slightly different spam emails producing the same checksum.