The encrypted image retrieval technique allows users to retrieve images in an encrypted manner without decrypting images. However, most of the existing schemes still are vulnerable to security threats and inefficiency, caused by malicious users and inefficient feature extraction methods, respectively. To this end, we propose a traceable encrypted image retrieval in the multi-user setting in this article, termed as MU-TEIR. First, MU-TEIR employs a convolutional neural network VGG16 to extract image feature vectors and calculate the mean and variance of the feature vectors to construct the index, then encrypts index with the distributed two trapdoors public-key cryptosystem. After that, MU-TEIR protects image content by encrypting each image pixel with a standard stream cipher. Furthermore, MU-TEIR utilizes a watermark-based mechanism to prevent malicious query users from maliciously distributing images. Detailed security analysis shows that MU-TEIR protects the outsourced images and indexes security as well as query privacy, and can track malicious users. Experimental results verify effectiveness of MU-TEIR.

中文翻译：

---

MU-TEIR：多用户环境下可追溯的加密图像检索


加密图像检索技术允许用户以加密的方式检索图像，而无需解密图像。然而，大多数现有方案仍然容易受到恶意用户和低效特征提取方法造成的安全威胁和效率低下。为此，我们在本文中提出了一种多用户环境下可追溯的加密图像检索，称为 MU-TEIR。首先，MU-TEIR采用卷积神经网络VGG16提取图像特征向量并计算特征向量的均值和方差来构造索引，然后使用分布式二陷门公钥密码系统对索引进行加密。之后，MU-TEIR 通过使用标准流密码加密每个图像像素来保护图像内容。此外，MU-TEIR利用基于水印的机制来防止恶意查询用户恶意分发图像。详细的安全分析表明，MU-TEIR可以保护外包图像和索引的安全以及查询隐私，并且可以跟踪恶意用户。实验结果验证了MU-TEIR的有效性。