Image encryption based on flexible computing of chaotic systems
This work addresses a specific problem in cryptography for secure image transmission, but it is incremental as it builds on existing chaotic systems with a computational improvement.
The paper tackled the loss of chaotic properties in image encryption due to finite computer precision by applying interval analysis to the Lorenz System, resulting in superior correlation and entropy indexes compared to recent literature.
The increase in data traffic on the internet has significantly increased the relevance of data and image encryption. Among the techniques most used in cryptography, chaotic systems have received great attention due to their easy implementation. However, it has recently been observed that these systems can lose their chaotic properties due to the finite precision of computers. In this work, we intend to investigate flexible computing tools, particularly interval analysis, to reduce this problem. We opted for the Lorenz System, as it is one of the few systems whose chaoticity is proven analytically. The results of this study, based on the correlation and entropy indexes, were superior to other studies published in the recent literature.