Abstract: System, method and process for securing and protecting data and data backups from cyberattack and implementing disaster recovery using machine learning and artificial intelligence. Embodiments learn and establish baseline parameters of routine, normal and non-compromised behavior and activity of virtual machines operative in cloud ecosystem, detect and recognize anomalous events related to advanced persistent threats to the instance, such as ransomware, and automatically implement preconfigured actions as determined by a user with the primary objective of protecting data and data backups.

Abstract: A method including the steps of selecting an n-ink model for a color device, for transferring a set of colorant values in colorant space to a set of color values in color space; selecting a printer characteristic of the n-ink model, wherein the printer characteristic indicates the regularity of the n-ink model; evaluating, for the n-ink model, a set of one or more values and/or ranges for the printer characteristic, thus determining the regularity of the n-ink model; and modifying the n-ink model such that the modified n-ink model is regular, if, based on the evaluation, the n-ink model was not regular.

Abstract: A method including the steps of selecting an n-ink model for a color device, for transferring a set of colorant values in colorant space to a set of color values in color space; selecting a printer characteristic of the n-ink model, wherein the printer characteristic indicates the regularity of the n-ink model; evaluating, for the n-ink model, a set of one or more values and/or ranges for the printer characteristic, thus determining the regularity of the n-ink model; and modifying the n-ink model such that the modified n-ink model is regular, if, based on the evaluation, the n-ink model was not regular.