遥感图像具有多时相、多语义、多波段等特点,鉴于敏感遥感图像涉及国家机密信息及传统图像搜索效率低下的原因,利用云平台进行遥感图像安全外包搜索已是大势所趋。因此提出了一种加密遥感图像的安全外包搜索方案,对存储在云平台的遥感图像进行扫描模式加密,再通过异或(XOR)运算和Johnson-Lindenstrauss (JL)转换得到一份双密文,JL转换的遥感图像用于在云平台进行搜索,XOR运算后的遥感图像用于图像解密。实验结果表明,本文方案可以有效保证云平台上遥感图像的安全性,同时,加密图像搜索的准确率高, 搜索效率较同态加密提升98.37%, 且计算复杂度低, 通信成本低, 适合于云计算平台部署应用。

The remote sensing images have the multi-temporal, multi-semantics and multi-spectral characteristics. In view of the sensitive remote sensing images involving state secret information with low searching efficiency, it is a general trend to conduct a secure outsourcing search for remote sensing images based on a cloud platform. Thus, a scheme of secure outsourcing search for encrypted remote sensing images is proposed. The remote sensing image stored on the cloud platform is first encrypted by the scan mode, and then a double ciphertext is obtained through the exclusive or operation and the Johnson-Lindenstrauss (JL) transformation. The JL-transformed remote sensing images are used to search on the cloud platform, while the exclusive or encrypted remote sensing images are used to decrypt image. The experimental results show that this scheme can effectively guarantee the security of remote sensing images on the cloud platform. Meanwhile, the search accuracy of encrypted images is high and the search efficiency is 98.37% higher than that by homomorphic encryption. Moreover, the computational complexity and communication cost are low, and it is suitable for the deployment on the cloud computing platforms.