Abstract: When the traditional grey neural network combination prediction algorithm predicted the intrusion information in the network, it lacked the preprocessing process of low matching degree heterogeneous information, did not predict the intention of information intrusion attack, and had some problems, such as low prediction accuracy and poor intrusion prevention performance. We proposed a new intrusion awareness prediction algorithm for mobile network with low matching degree heterogeneous information in cloud computing environment, and preprocessed the low matching degree heterogeneous information of initial network by grey model. Firstly, the intrusion attack intention matrix was obtained by using the intrusion awareness prediction algorithm with low matching degree heterogeneous information based on metapath. Then, according to the matrix, the function relationship of intrusion attack intention was obtained, and intrusion attack intention prediction with the low matching degree heterogeneous information was realized. The experimental results show that the proposed 
algorithm can fully predict the intention and process of the information intrusion, the success rate of the defense for intrusion information node is about 85%, the false alarm rate and the missed alarm rate are low, and the prediction accuracy is high.

Key words: cloud computing platform, mobile network, low matching , degree heterogeneous information, [JP] intrusion awareness prediction, preprocessing, intrusion attack intention, metapath