In order to make online handwritten signature verification more practical, this paper presents a method based on Discrete Cosine Transform (DCT) frequency analysis and Support Vector Data Description (SVDD). Signature data is collected by Android mobile phone software, and then extracts signature features based on DCT frequency analysis and Singular Value Decomposition (SVD). The online signature verification is established based on SVDD, for which is suitable for the small amount sample and one-class classification method, and uses the grid search method to optimize the kernel function parameters. The experimental results show that this method is efficient, has a low complexity, can extract the signature features clearly, and obtains a better recognition effect with a small amount of a real signature as the training sample.