In distributed systems

some traditional association rules mining algorithms have been developed with all original data being gathered into a centralized site.However

these algorithms are not fit for the situation where no user is willing to disclose his information.In the privacy preserving association rule mining problems

there are several participants engaged in the computation and the algorithms are run on the union of their databases.Currently

the secure union algorithm can be used to protect each user's privacy if all the user's databases have the same structure.However

in secure union algorithm

each participant should encrypt all the participants' data.So

if there are many participants engaged in the cooperative computation

this method is inefficient.Thus

in this paper

we introduce a data disguised method for privacy preserving association rule mining based on the randomized response techniques

present the mining algorithm on the disguised item set and analyze the complexity of this algorithm.The experiments show that the rule that this algorithm gets has fewer relative error which is less than 2% compared with the original rules.We also give some values of the parameters which make the relative error is the lowest.