Confidential dominance relation based rough set is a model of incomplete ordered information processing, computation of approximations of which is a core issue. In real-life applications, the attribute set is dynamically changed. According to the variation of the attribute set, confidential dominance and dominated class are firstly calculated. Then the principles of incremental updating approximations are discussed when some attributes are added or deleted. Furthermore, incremental approaches and algorithms in the confidential dominance relation based on rough set are proposed. Finally, the experiments on UCI datasets developed on Matlab are designed to evaluate the performance of the proposed incremental updating method and non-incremental updating method. The results show that the proposed algorithms are effective and feasible under the variation of the attribute set.