Nowadays, an unprecedented volume of data is shared and stored across various digital platforms and the volume is bound to intensify even further in the future. This proliferation and accessibility of data contributes to convenience in our lives and enables innovation and advancement that weren't achievable in the past; however, it also brings a concerning challenge to the security of information. Steganography, derived from the Greek words "steganos" (covered) and "graphein" (writing), aims to hide the secret information inside a cover data resulting in stego data, also called the container. Unlike cryptography, which investigates in hiding the data of interest in a coded form, steganography operates with imperceptible concealment so that the existence of the secret data is undetectable. Up to now, image is the most commonly used modality of cover data, as it is less sensitive to human perception and is comparatively simple to embed secret information.

Over 5000 Dynamic World image are produced every day, whereas traditional approaches to building land cover data can take months or years to produce. As a result of leveraging a novel deep learning approach, based on Sentinel-2 Top of Atmosphere, Dynamic World offers global land cover updating every 2–5 days depending on location. A major benefit of an AI-powered approach is the model looks at an incoming Sentinel-2 satellite image and, for every pixel in the image, estimates the degree of tree cover, how built up a particular area is, or snow coverage if there's been a recent snowstorm, for example. As a result of the European Commission's Copernicus Program making European Space Agency Sentinel data freely and openly available, products like Dynamic World are able to offer 10m resolution land cover data. This is important because quantifying data in higher resolution produces more accurate results for what's really on the surface of the Earth.