A trustworthiness-based distribution model for data leakage prevention

Abstract

Under the global circumstances where data leakage gets more and more severe, we present a trustworthiness-based distribution model that aims at data leakage prevention (DLP). In our model, first, the distributor calculates the user’s trustworthiness based on his historical behaviors; second, according to the user’s trustworthiness and his obtained file set overlapping leaked file set, the distributor accesses the probability of the user’s intentional leak behavior as the subjective risk assessment; third, the distributor evaluates the user’s platform vulnerability as an objective element; last, the distributor makes decisions whether to distribute the file based on the integrated risk assessment. The experiments indicate that the model can distinguish users of different types and make the probability of malicious users’ requirements being denied much higher than that of honest users’ requirements being denied, so that the model is capable of preventing data leakage validly.