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AES S-Boxes in depth
AES S-Boxes in depth

... • The finite field element {00000010} is the polynomial x, which means that multiplying another element by this value increases all it’s powers of x by 1. This is equivalent to shifting its byte representation up by one bit so that the bit at position i moves to position i+1. If the top bit is set p ...
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... For Steel Wire, we’d have 182/26 = 7 Pieces of Steel. Note that we’d have 12 Total Pieces of Wire , as described above. [DC32] This is the LCM(120, 220), which we assume we could show ALL the work as described in class and in [DC28], for example. Note the LCM(120, 220) = 1320, so the answer is: 1320 ...
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... For Steel Wire, we’d have 182/26 = 7 Pieces of Steel. Note that we’d have 12 Total Pieces of Wire , as described above. [DC32] This is the LCM(120, 220), which we assume we could show ALL the work as described in class and in [DC28], for example. Note the LCM(120, 220) = 1320, so the answer is: 1320 ...
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... For Steel Wire, we’d have 182/26 = 7 Pieces of Steel. Note that we’d have 12 Total Pieces of Wire , as described above. [DC32] This is the LCM(120, 220), which we assume we could show ALL the work as described in class and in [DC28], for example. Note the LCM(120, 220) = 1320, so the answer is: 1320 ...
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Factorization



In mathematics, factorization (also factorisation in some forms of British English) or factoring is the decomposition of an object (for example, a number, a polynomial, or a matrix) into a product of other objects, or factors, which when multiplied together give the original. For example, the number 15 factors into primes as 3 × 5, and the polynomial x2 − 4 factors as (x − 2)(x + 2). In all cases, a product of simpler objects is obtained.The aim of factoring is usually to reduce something to “basic building blocks”, such as numbers to prime numbers, or polynomials to irreducible polynomials. Factoring integers is covered by the fundamental theorem of arithmetic and factoring polynomials by the fundamental theorem of algebra. Viète's formulas relate the coefficients of a polynomial to its roots.The opposite of polynomial factorization is expansion, the multiplying together of polynomial factors to an “expanded” polynomial, written as just a sum of terms.Integer factorization for large integers appears to be a difficult problem. There is no known method to carry it out quickly. Its complexity is the basis of the assumed security of some public key cryptography algorithms, such as RSA.A matrix can also be factorized into a product of matrices of special types, for an application in which that form is convenient. One major example of this uses an orthogonal or unitary matrix, and a triangular matrix. There are different types: QR decomposition, LQ, QL, RQ, RZ.Another example is the factorization of a function as the composition of other functions having certain properties; for example, every function can be viewed as the composition of a surjective function with an injective function. This situation is generalized by factorization systems.
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