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Fragile Watermarking based on Linear Cellular Automata using Manhattan Distances for 2D Vector Map

There has been a growing demand for publishing maps in secure digital format, since this ensures the integrity of data. This had lead us to put forward a method of detecting and locating modification data that is extremely accurate and simultaneously guarantees that the exact original content is recovered. More precisely, this method relies on a fragile watermarking algorithm that is developed in accordance with a frequency manner and, for every spatial feature, it can embed hidden data in 2D vector maps. The current paper proposes a frequency data-hiding scheme, which will be examined in accordance with Linear Cellular Automata Transform using Manhattan distances. Various invertible integer mappings are applied in order to find out the Manhattan distances from coordinates. To begin with, the original map is transformed into LCA, after which the watermark insertion process is carried out to transform the coefficient of the transformation result frequency into LSB. Lastly, a watermarked map is created by applying the inverse LCA transform, meaning that a LCA-transformed map is produced. Findings indicate that the suggested method is effective since in terms of invisibility and the capacity to allow for modifications. The methods also allow the detection of modification data, the addition and removal of some features, and enable the exact original content from the 2D vector map to be included.