Abstract: Current research on differential private publication associcted with data stream mainly considers a binary data stream, which cannot efficiently deal with the general data stream’s private publication. An efficient differential private histogram publication algorithm called DDPA was proposed, which is oriented toward non-uniform distributed numerical stream. Basing on the sliding window model, the similarity on two adjacent timestamps of data distribution is applied to allocate the budget privacy dynamically, which makes each window’s total budge not exceed the privacy budget ε, and after that, the grouping and merging strategies are used to calculate the local optimal histogram quickly. According to comparing and analyzing the proposed algorithm with the other similar algorithms on the published data’s availability, the experimental results show that the proposed algorithm is effective and feasible.

Key words: differential private, data stream, histogram publication