Data Generation:
Every possible file that will ever exist is just a combination of pre-defined characters. By cycling through all possible combinations, every file that can ever exist can be created. Computers are not fast enough to do this effectively (not even close), but it remains an interesting fantasy. Data generation can be defined as the process of combining raw data characters to create new data, and indirectly create content. Data generation allows skipping the traditional process of content creation, and going directly to having the end result. Every blockbuster movie that exists, or ever will exist can be generated. Every piece of software in use in the world today, and all the updates that haven't been coded yet can be generated. Documents detailing a cure for every disease, advances in the designs of space craft, and answering every question mankind has ever asked can be generated. Video footage you forgot to record of your family vacation, and footage of family vacations you never took can be generated. However, major advances in computers, data generation techniques (including advances in targetting and profiling), and artificial intelligence are needed before data generation becomes a viable for anything beyond basics like creating password files, or static files (files of meaningless data). This is because there is an immense number of possible combinations, and the vast majority yield static (garbage data).
Exploring combinations in a range is called an attack. There are two types of attacks random, and sequential. Random being creating random combinations. Sequential meaning exploring combinations in order, as dictated by the method being used. In addition, attacks may have further constrants applied such as a target, and profiles. A target is general constraint that applies to raw data (eg: a targetting a file type, or data type). A profile is a target specific constrant (eg: the target is image files, and the profile restricts combinations to those valid for those file types, or even limits which colors can occur where in the image). Profiles largely emulate manipulations which can occur when performing content generation (eg: random image generators which are based on content generation may ensure valid colors are created by only working with those values as possible outcomes).
Content Generation:
Content generation is the process of combining valid content specific characters (or sets of characters) to create new content. It's very similar to data generation except instead of dealing with raw data, it deals directly with content. Content generation is used in the world today to create dummy text (eg: lorem ipsum), random images, and passwords.
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Authors:James Daniel Marrs Ritchey
License:Ritchey Permissive License v8
Ritchey Permissive License v8:
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