A Level Inference Method for Aggregated Information of Objects Based on Clustering Analysis

The relations among objects with secure level are very complex, which leads to the problems of security in multi-level network, such as information leakage by object aggregation. This paper puts forward a level inference method for aggregated information of objects based on clustering analysis. This method makes the reduction of attributes by the importance degree of attribute in one object, and attribute vector is formed. Then, according to formal concept analysis, this method accomplishes comparability analysis of objects in the same secure domain by gravity among concepts so that objects can be aggregated. Finally, according to probability estimate of fuzzy set about secure level of attributes or sets of attribute, probability of higher level information inferred by aggregation of similar objects is computed, which may effectively establish access control policy in multi-level network, and accomplish restricted access of congeneric objects in order to reduce the risk of information system.