To achieve the goal that personal and original information is not disclosed to each other when several parties cooperatively mine several data tables at different computational sites, based on secure triple-party protocol, a triple-site cross multi-table frequent item sets mining algorithm with privacy preserving was proposed in distributed environment with multiple tables at each site. The proposed algorithm disturbed data by generating random numbers, mined frequent item sets of inter-site in parallel, and linked the data with equal-value by common link attribution of the tables among the sites and applied secure protocol to compute the global support of inter-site cross-table frequent item sets. The experimental results show that the proposed algorithm is efficient, and it can not only mine the cross multi-table frequent item sets, but also preserve the private data at each site.