Paraphrase identification is the task of identifying automatically whether a pair of sentences carries the same meaning. In this paper, we propose a deep learning system for paraphrase identification of tweets. The proposed system integrates the state-of-the-art features and Gated Recurrent Units to extract high level features of two tweets and identify whether they are identical. The effectiveness of the proposed system has been evaluated by using it in the supervised task of paraphrase in Twitter that presented in SemEval 2015, obtaining results which show its superiority over the state-of-the-art systems.