There are many problems in the traditional data privacy protection algorithm

such as long execution time

high concealment and poor adaptability. The proposed network data density clustering algorithm based on privacy protection

in the big data environment

the transformation function generates a random given the big data environment of network privacy data

then use the numerical transform function of network privacy data are changed

and the numerical transform as the result of random response then according to the characteristics of the network; the network node density clustering analysis

generated in accordance with any size and shape of the clusters

through the data network privacy and network privacy quantitative information loss data structure information for effective analysis of data privacy loss amount; and finally into the real network node in the successful generation of cluster

through increasing etc. technology

complete privacy protection of network information. The simulation results show that the proposed algorithm has a better privacy protection effect

and it has a good adaptability to the attack of a variety of different background knowledge.