Abstract: Aim to address the problem of anonymization on data streams, an anonymization algorithm based on time density for data stream was proposed. Time weight and time density were designed for describing the data stream’s temporal, when the published clusters reach the threshold, it will delete the minimum time density cluster to ensure the availability of published clusters. Furthermore, in order to maintain the higher efficiency, the algorithm scans the data only once to satisfy the anonymization requirements for speeding up. The experimental results on the real dataset show that the algorithm is efficient and effective meanwhile the quality of the output data.