Application of Context to Fast Contextually Based Spatial Authentication Utilizing the Spicule and Spatial Autocorrelation

This paper proposes an integrating mathematical method that unifies a new Contextual Processing model with that of the Spicule visual authentication method. In previous work the Spicule has been initially determined to be much faster at generation of authentication signatures for spatial data than standard encryption methods. It however could be much faster than it already is if a method was designed that could reduce the number of spatial objects it has to generate authentication signatures for. Previous experiments required Spicule to authenticate all spatial objects in a set for comparison against encryption methods. This paper provides brief overviews and background on the Spicule, and the new Contextual Processing model. It then proceeds to present the integrating mathematical approach of localized spatial autocorrelation. Finally an algorithm and the overall application of the method is presented by which limited sets of spatial object are mathematically selected for authentication when they are germane to a spatial query.