Metadata-Version: 2.4
Name: isoring
Version: 0.0.3
Summary: A structure for data security and a cracking environment.
Home-page: https://github.com/Changissnz/isoring
Author: Richard Pham
Author-email: Richard Pham <phamrichard45@gmail.com>
License-Expression: MIT
Project-URL: Homepage, https://github.com/changissnz/isoring
Project-URL: Issues, https://github.com/changissnz/isoring/issues
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: author
Dynamic: home-page
Dynamic: license-file

# isoring
a component from the terminated project, puissec. 

A structure called the `IsoRingedChain` is supposed to guard a big secret, comprised of a sequence 
of arbitrarily-lengthed vectors (secrets). 

# What is a Secret? 

Who knows, really?  

In this computer program, a secret is represented by a finitely lengthed vector. The `Sec` structure contains this vector of 
length `n`, as well as `k` additional vectors in the same dimension of `n`. These `k+1` vectors are the local optima of 
`n`-space in real numbers. Every one of those vectors has an associated probability value, the probability values adding up 
to one. These probability values can be arbitrary, meaning the actual secret (vector) of `Sec` may have any probability 
value in `[0,1.]`. Design of `Sec` is based on the common machine-learning problem of choosing local optima over the best 
solution. 

The `IsoRing` structure contains the secret, a vector in finite space. It contains that secret in one `Sec` instance. 
`IsoRing` also holds an additional `j` `Sec` instances, each of these `Sec` instances in a unique finite vector 
dimension. These `j` instances serve as buffers to third-party acquisition of the actual `Sec` instance. In effect, 
`IsoRing` has two primary layers of defenses: the `j` `Sec` instances and the `r_j >= 1` alternative local optima to 
the actual vector of some `Sec`. 

At any point in program run, outward representative of `IsoRing` is exactly one `Sec` instance, the isomorphic 
representation (iso-repr). 

In order for a third-party to interact with an `IsoRing` for information, third-party will have to interact with 
feedback function of `IsoRing`. For an `IsoRing` in iso-repr vector dimension `q`, feedback function provides a 
`q`-vector of distance scores. Distance scores are conventionally euclidean point distances. However, there are 
alternative feedback functions that provide distorted distance scores via pseudo-random number generator. 

For a sequence of arbitrarily-lengthed vectors (secrets), an `IsoRingedChain` is used to cover it and this structure 
is, in turn, composed of a number of `IsoRing`s equal to the number of those vectors (secrets). 

# What is an Isomorphic Ringed Chain? 

An `IsoRingedChain` guards a sequence of vectors (secrets). Any of the `IsoRing`s in an `IsoRingedChain` may be in 
an isomorphic representation not of the same dimension of the actual secret. Additionally, every `IsoRing` in an 
`IsoRingedChain` has dependencies and co-dependencies in order for third-party access to it. Dependencies are the 
`IsoRing`s that must have been "cracked" by the third-party before getting to it, and co-dependencies are the 
`IsoRing`s that must be "cracked" alongside it. Cracking cannot proceed by an ordering of the `IsoRing`s that 
violate the specified dependencies and co-dependencies linking these structures together for the `IsoRingedChain`. 

# What is Cracking? 

In this program, the `Cracker` structure is responsible for determining all the secrets of an `IsoRingedChain`. This 
process of determination is "cracking". The `Cracker` must attempt cracking in the order specified by all of the 
contained `IsoRing`s' dependencies and co-dependencies. Otherwise, program will halt `Cracker` midway, resulting in 
its failure. 

`Cracker` is given background information, `BackgroundInfo`, on the target `IsoRingedChain`.  

NOTE: There are deficits to this map design of background information. However, it was chosen because it avoids the 
      Curse of Dimensionality, one of a few major problems that plagued successful complete development of the 
      program `puissec`, found at `github.com/changissnz/puissec`. Program `puissec` was the predecessor of this 
      program `isoring`. Program `isoring` is, in fact, a simpler version of only part of the problems in the 
      conceptualization of `puissec`. 

`BackgroundInfo` has three main components.  
1. Hypothesis map,  
    `<Isoring> identifier -> <Sec> index -> <HypStruct>`.  
2. Suspected `IsoRing`-to-`Sec` map,  
    `<Isoring> identifier -> <Sec> index`.  
3. Order of cracking, a sequence with each element  
    `{set of co-dependent IsoRing identifiers}`.  

One deficit about design of this `BackgroundInfo` is the hypothesis map. Every `Sec` instance can have at 
most one hypothesis on it. And the `HypStruct` is focused on exactly one local optimum. 

`HypStruct` represents a hypothesis on a `Sec`, of vector dimension `k`, and has these attributes.  
1. Suspected optima index `i` of the `Sec`.  
2. Bounds (a `k x 2` matrix) suspected to contain optima `i`.  
3. Hop size `h`, an integer, uniformly partitioning the bounds into `k x h` points.  
4. Probability marker `P`, used to cross-reference with probability output value `P'` from a 
   cracked `Sec`.  

The probability values in this program are meant to be reference values for a `Cracker`. If a `Cracker` 
uses a `HypStruct` to crack `Sec`, and the output probability from `Sec` differs from that of the 
`HypStruct` used, then the `Cracker` does not accept the cracking vector as the actual secret. 

NOTE: these are information games, broadly speaking.  

For every `IsoRing` being targeted by a `Cracker`, `Cracker` uses one `Crackling` at any one time, in 
order to attempt to crack the `IsoRing` for the vector (secret) of the `IsoRing`'s suspected `Sec`. A 
`Cracker` will attempt to use as many `Crackling`s, in re-cracking sessions, for an `IsoRing` as program 
permits until `Cracker` cracks its wanted local optimum from the suspected `Sec` of said `IsoRing`. 

A structure called a `SearchSpaceIterator` is employed by every `Crackling` to execute brute-force 
cracking attempts on an `IsoRing`'s isomorphic representation. `SearchSpaceIterator` outputs `k x h` 
points that uniformly cover the input bounds of matrix `k x 2`. 

If the `Cracker` does not a `HypStruct` for the `IsoRing`'s isomorphic representation (the second 
layer in the three-layer hypothesis map), program halts `Cracker` midway. If the `Crackling` is 
successful in cracking the isomorphic representation, `IsoRing` has to switch its isomorphic representation 
to an uncracked `Sec`. If there are none that have not been cracked, `IsoRing` stops switching its 
isomorphic representation due to the `Cracker` no longer being interested in cracking it anymore. 

If a `Crackling` does not produce any (vector, associated probability value) on a `Sec`, `Cracker` cannot 
proceed to attempting to crack any `IsoRing`s dependent on the `IsoRing`, pertaining to said `Sec`, being 
cracked. In most cases, `Cracker` would be halted. 

# The Brute-Force Environment 

There Are Rules To The Game. The rules are enforced in the environment `BruteForceEnv`, where a `Cracker` 
attempts to crack an `IsoRingedChain`. A `Cracker` is granted some arbitrary amount of energy, a real number. 
If the energy falls to zero or below, program halts `Cracker`. A `Cracker` can use only `t` number of 
`Crackling`s at once. If there are co-dependent `IsoRing` sets in `IsoRingedChain` that are greater in size 
than `t`, successfully cracking the `IsoRingedChain` is impossible for the `Cracker`. 

# What is Successful Cracking? Complete Execution or Complete Acquisition of Actual? 

The complete execution of cracking all the `IsoRing`s in an `IsoRingedChain` can be known by a `Cracker` by 
the time the program halts `Cracker`. However, the `BackgroundInfo` of a `Cracker` is what allows it to verify 
on what the actual vectors from `IsoRingedChain` are. 

# Additional Features 

Generative methods, found in this program, can be used to produce the relevant data structures. These 
methods do come in handy since there are a lot of variables to type up by hand.  

# An Example On the User Interface 

![Screenshot](screeshantaya.png) 
