As for that existing personalized privacy anonymous technology can not solve the problem that the numerical sensitive attribute is vulnerable to the proximity breach, an anonymous model called (ε_i, k)-anonymity model is proposed and the model is based on clustering technology. Firstly, the model divides the sensitive attribute values in ascending order into several sub-intervals based on the clustering method; then, it proposes an (ε_i, k)-anonymity principle for numerically sensitive attributes against proximity breach; finally, a maximum bucket-first algorithm is proposed to implement the (ε_i, k)-anonymity principle. The experimental results show that compared with the existing scheme used for resisting proximity breach, the information loss of the proposed anonymous scheme is reduced, the algorithm execution efficiency is improved and it can reduce the leakage risk of user privacy effectively.