LAUSR

Commutative encryption and watermarking (CEW) can provide comprehensive protection for vector data in geographical information system (GIS) by integrating encryption and watermarking. However, the existing CEW methods for image or video are not suitable for GIS vector data. These CEW methods are still unable to ensure independence between encryption and watermarking for GIS vector data. To solve this problem, this paper proposes a new CEW method based on singular value decomposition (SVD) for GIS vector data. Firstly, the characteristics of SVD are analyzed for GIS vector data. Then, the singular values are selected as the feature invariant. The stability and independence of the singular values are used for embedding watermark and the orthogonal invariance of the singular values is used for encryption. The experimental results show that the proposed method can achieve the independent of encryption and watermarking, as well as strong robustness and high security for commutative encryption and watermarking. The partial decryption can also be realized by the proposed method, which can achieve the network security real-time decryption for GIS vector data.