Techniques for efficiently determining similarity hashes
Abstract:
Techniques for data processing may include: receiving a data block P having a binary representation; determining features for the data block P; determining, using at least one table of precomputed hash values, feature hashes for the features, wherein each of the feature hashes corresponds to a different feature, wherein each of the feature hashes is one of the precomputed hash values of the at least one table; and determining, in accordance with the feature hashes, a similarity hash for the data block P. Each feature may be a byte of P. The at least one table may be a single 3 dimensional or multiple 2 dimensional tables. Each row of a table of precomputed hash values may correspond to a single precomputed hash value. The row may include byte entries where each byte entry includes a single bit value of a precomputed hash.
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