Fractal Encryption

Fractal Encryption

I've heard that one can encrypt data using drawings of the Mandlebrot set, and that this encryption algorithm is quantum-safe (can't be broken with a quantum computer, unlike many commonly-used algorithms). I looked around on Google for more information but I've only come across some articles intended for a more non-technical audience. Does anyone have any sources on this that I could use to learn more about this fascinating subject?

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7 Answers

First, the reason that most of the write-ups on the internet seem so obtuse is that they all appear to be drawn from a handful of patent applications. Patent applications for new formulas & algorithms always tend appear to be hiding something, because they are. It's notoriously difficult to police unlicensed use of such things and the applicants try to straddle the line between patent protection and trade secret protection. The point here is that it doesn't necessarily mean that it's all BS.

Secondly, all Fractal mappings that I know of are, to some extent or another "lossy", because the mapings are not strictly 1 to 1. While this is a good reason to beleive that there is no effecient way to break the code, it also means that anything directly "encrypted" by a lossy fractal, can not be decrypted either, even with the key. Thus any kind of direct fractal hashing is not reversible.

Therefore, Fratcal Encryption cannot mean that the message itself is directly encrypted with the fractal. Rather, it must mean that the fractal is used as a "master key" to enable simultaneous generation of "local" or "sequential" keys that are then used to encrypt and decrypt the actual messages.

Before we go any further, let's review the basics of encryption:

Encryption Algorithm Principles

Lets say you have a series messages M(j) for j=1 to N that you want to be able to transmit securely to a Receiving party. You'll need a reversible encryption function E like so:

E(M(j), k) --> X(j)

Where (k) is an encryption key and X(j) is the corresponding encrypted message. Then the message is transmitted to our receiver who has a complementary function E' to decipher the encrypted message:

E'(X(j), k) --> M(j)

However, AFAIK you cannot make both an E() and E'() function using Fractals. On the other hand, there are some functions, like XOR that are their own complements:

( M(j) XOR k ) --> X(j)  *and also* ( X(j) XOR k ) --> M(j)

But XOR is also a weak encryption function and although it is perfectly secure for a single message, if we use it more than once with the same key (k), it becomes very easy to reverse-engineer (k), thus making XOR unsafe for single key encryption systems. This can be solved by using a different key every time:

M(j) XOR K(j) --> X(j)

and

X(j) XOR K(j) --> M(j)

This solves one problem, but introduces another, which is, how do we insure that both sender and receiver have the same set of keys? Transmitting the series of keys is no solution because that takes us back to the original problem of securely transmitting a series of messages.

Instead we want to generate a series of identical keys on both the sender and receiver independently. But we need to be able to generate a series of keys that are cryptographically secure in their own right. That is, even if an external observer knew all of the preceding keys, they still would not be able to predict the next key in the series with any accuracy. And because we will need a completely different series of keys every time (to make them unguessable) we actually need the Key series itself to be key-based.

The solution to this is to use a Master Key MK, and a different encryption function H, to generate the specific keys for each message:

H(MK, j) --> K(j);  M(j) XOR K(j) --> X(j)

and

H(MK, j) --> K(j);  X(j) XOR K(j) --> M(j)

This is where our Fractals come in, because as we can see above, the H function does not need a complementary function H'. So we can freely use a Fractal-based function with a master key to generate our series of local keys.

David Miller
Author

David Miller

David Miller brings 15 years of experience in global economics, personal finance strategy, and market dynamics. He specializes in turning complex economic trends into actionable insights for everyday readers.