ChaotLang: A Graphical Domain-Specific Modeling Languagefor Chaotic Maps in cryptographic and Complexity Analysis

Résumé fourni par la source

Chaotic maps (CMs) are key components of chaos theory as they simulate systems whereby even the smallest changes to the initial circumstances can have significantly different results. Each map serves a mathematical function that converts an initial value into a random unexpected series of values. Nonetheless, despite the benefits of CM, there are a number of obstacles to consider. Firstly, accurately coding the CMs is a challenge for programmers. Other problems include generating a strong key and verifying its security features, accuracy and numerical stability, choosing parameters, and ensuring that the discretizing process is accurate. Moreover, it is often difficult to understand the results of a chaotic map simulation, as even the smallest changes can result in the emergence of a nonchaotic system. In the present work, an extensible modeling language that can be applied exclusively to CMs domain is proposed, namely ChaotLang, which has been developed to address the aforementioned challenges. By developing a meta-model based on the fundamental concepts of CMs and their connections, Chaotlang’s front-end compiler can be constructed. Additionally, by providing all components needed to produce CMs, hybridize them, and perform chaotic analysis, complexity measurements, randomness analysis, and plain input encryption using CMs, ChaotLang has the benefit of being graphically versatile and expressive. To assess ChaotLang, a set of key assessment criteria used to evaluate modeling languages were employed. Furthermore, two files containing 1000000 points each have been created to assess ChaotLang in terms of its performance as an execution-and-analysis platform, based on the Henon map.

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