How to calculate the inverse key matrix in Hill Ci

Question

I am finding it very hard to understand the way the inverse of the matrix is calculated in the Hill Cipher algorithm. I get the idea of it all being done in modulo arithmetic, but somehow things are not adding up. I would really appreciate a simple explanation!

Consider the following Hill Cipher key matrix:

 5 8 
17 3

Please use the above matrix for illustration.

Answer 1

You must study the Linear congruence theorem and the extended GCD algorithm, which belong to Number Theory, in order to understand the maths behind modulo arithmetic.

The inverse of matrix K for example is (1/det(K)) * adjoint(K), where det(K) <> 0.

I assume that you don't understand how to calculate the 1/det(K) in modulo arithmetic and here is where linear congruences and GCD come to play.

Your K has det(K) = -121. Lets say that the modulo m is 26. We want x*(-121) = 1 (mod 26).
[ a = b (mod m) means that a-b = N*m]

We can easily find that for x=3 the above congruence is true because 26 divides (3*(-121) -1) exactly. Of course, the correct way is to use GCD in reverse to calculate the x, but I don't have time for explaining how do it. Check the extented GCD algorithm :)

Now, inv(K) = 3*([3 -8], [-17 5]) (mod 26) = ([9 -24], [-51 15]) (mod 26) = ([9 2], [1 15]).

Update: check out Basics of Computational Number Theory to see how to calculate modular inverses with the Extended Euclidean algorithm. Note that -121 mod 26 = 9, so for gcd(9, 26) = 1 we get (-1, 3).

Answer 2

In my very humble opinion it is much easier to calculate the inverse matrix (modular or otherwise) by using the Gauss-Jordan method. That way you don't have to calculate the determinant, and the method scales very simply to arbitrarily large systems.

Just look up 'Gauss Jordan Matrix Inverse' - but to summarise, you simply adjoin a copy of the identity matrix to the right of the matrix to be inverted, then use row operations to reduce your matrix to be solved until it itself is an identity matrix. At this point, the adjoined identity matrix has become the inverse of the original matrix. Voila!