Every day social multimedia applications generate millions of images. To handle such huge amount of images, an optimal solution is using the public cloud, since it has powerful storage capability. Images usually contain a wealth of sensitive information, therefore social service providers need not only to provide services such as retrieval and sharing but also to protect the privacies of the images. In this paper, we propose a privacy-preserving scheme for content-based image retrieval and sharing in social multimedia applications. First, the users extract visual features from the images, and perform locality-sensitive hashing functions on visual features to generate image profile vectors. We then model the retrieval on the images as the equality search on the image profile vectors. To enable accurate and efficient retrieval, we design the secure index structure based on cuckoo hashing, which has constant lookup time. To meet the requirements of dynamic image updating, we enrich our service with image insertion and deletion. In order to reduce the key management overhead and the access control overhead in social applications, we process keys using secret sharing techniques to enable the users holding similar images to query and decrypt images independently. Finally we implement the prototype of the proposed scheme, and perform experiments over encrypted image databases. INDEX TERMS Image retrieval, image sharing, multimedia, privacy-preserving.

Nowadays, several image-based smart services have been widely used in our daily lives, generating many digital images. Since smart devices outsource digital images to the cloud, researchers prefer to select some desired targets from the massive images within the cloud for analysis and improve smart services. Therefore, protective image retrieval on the cloud has attained maximum concentration for privacy-preserving purposes, and the availability assurance of images on the cloud is also a crucial link. Ensuring image security and availability in the cloud environment and precisely preserving retrieval accuracy is comes as a utilitysecurity dilemma while few existing works have explicitly addressed it. Therefore, this paper proposes privacy-preserving image retrieval in the distributed environment based on the combination of image encryption for similarity search and secret image sharing. On the basis of them, we define two-stage encryption. The first-stage encryption algorithm is introduced by modifying Wolfram's reversible cellular automata-based image encryption, which can create a set of processing images to ensure image security and retrieval accuracy. Then, the second-stage encryption algorithm is put forward based on secret image sharing to improve image security and availability. The color histogram could be extracted from the encrypted images for similarity retrieval, and the shadows could be

With the development and innovation of new techniques for 5G, 5G networks can provide extremely large capacity, robust integrity, high bandwidth, and low latency for multimedia image sharing and storage. However, it will surely exacerbate the privacy problems intrinsic to image transformation. Due to the high security and reliability requirements for storing and sharing sensitive images in the 5G network environment, verifiable steganography-based secret image sharing (SIS) is attracting increasing attention. The verifiable capability is necessary to ensure the correct image reconstruction. From the literature, efficient cheating verification, lossless reconstruction, low reconstruct complexity, and high-quality stego images without pixel expansion are summarized as the primary goals of proposing an effective steganography-based SIS scheme. Compared with the traditional underlying techniques for SIS, cellular automata (CA) and matrix projection have more strengths as well as some weaknesses. In this paper, we perform a complimentary of these two techniques to propose a verifiable secret image sharing scheme, where CA is used to enhance the security of the secret image, and matrix projection is used to generate shadows with a smaller size. From the steganography perspective, instead of the traditional least significant bits replacement method, matrix encoding is used in this paper to improve the embedding efficiency and stego image quality. Therefore, we can simultaneously achieve the above goals and achieve proactive and dynamic features based on matrix projection. Such features can make the proposed SIS scheme more applicable to flexible 5G networks. Finally, the security analysis illustrates that our scheme can effectively resist the collusion attack and detect the shadow tampering over the persistent adversary. The analyses for performance and comparative demonstrate that our scheme is a better performer among the recent schemes with the perspective of functionality, visual quality, embedding ratio, and computational efficiency. Therefore, our scheme further strengthens security for the images in 5G networks.

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Substring searching on gene sequence data is widely used for analyzing the association between a list of gene mutations and a specific disease. As substring search usually has a high computational cost, deploying it in the cloud has become a popular solution. Moreover, the cloud allows easier data sharing among medical organizations. Since the gene data contains private information, medical organizations usually outsource encrypted gene data to the cloud and selectively share with others. Most existing solutions for the privacy-preserving substring search problem are based on searchable encryption. However, they mainly focus on single-source gene data, not suitable for handling multi-source gene data because of some practical weaknesses. In this paper, we propose a cryptographic scheme that supports privacy-preserving substring search on multi-source encrypted gene data. The cloud can authorize queriers with access control and perform substring searches over the multi-source encrypted gene data for them. Despite the outsourced gene data is encrypted with different keys, but the authorized querier can issue a substring search only uses its own key. We adopt the composite order bilinear map as the primary underlying cryptographic primitive of our scheme. We mainly focus on protecting the privacy of the outsourced gene data and the substring queries, and we provide a security analysis under the honest-but-curious model. We also perform experiments on different datasets and analyze the experimental results in terms of computation cost and communication cost. The analyses show that our scheme is secure and efficient for substring search on multi-source encrypted gene data. INDEX TERMS Composite order bilinear map, data privacy, gene data, substring search.

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