Abstract:

Detecting sensitive information on terminal documents becomes extremely important due to the potential risk of sensitive information leakage. In order to resolve the problems of imprecise document model caused by context-free index and inadequate semantic extension, firstly, a context-sensitive document smoothing algorithm was proposed to build document index, which can retain much more document information; secondly, combining the sensitivity of concept in the domain ontology, semantic extension was improved to expand the detection range of sensitive information; finally, document smoothing and query expansion were integrated into the language model, and a sensitive information detection approach based on the language model was proposed. Comparative experiments on four approaches using different index mechanisms, query expansion algorithms and detection models, the recall, precision and F-Measure of the proposed approach were 0.798, 0.786 and 0.792 respectively, and the various performance indicators were obviously better than the compared algorithms. The experimental results show that the proposed approach is a more effective one.