In order to improve the security performance of network cloud storage data and evaluate the risk of data security, an information security risk assessment model of cloud storage data is proposed based on grey neural network. The information security risk data to be analyzed and evaluated is classified based on the autonomic tuples division method and Gaussian density spectrum estimation is used to extract the information features, and then information is decomposed by the grey neural network, at last, the adaptive differential evolution method is used to detect the correlation of the information. According to the feature extraction of information security risk data spectrum, the correlation compensation and adaptive control are realized to improve the ability of information security risk assessment. The safety evaluation curve can converge quickly. Compared with the KNN method, the simulation results show that this method has higher accuracy. So, it’s better protection ability to protect big data security.