Reversible data hiding in ciphertext has potential applications for privacy protection and transmitting extra data in a cloud environment. For instance, an original plain-text image can be recovered from the encrypted image generated after data embedding, while the embedded data can be extracted before or after decryption. However, homomorphic processing can hardly be applied to an encrypted image with hidden data to generate the desired image. This is partly due to that the image content may be changed by preprocessing or/and data embedding. Even if the corresponding plain-text pixel values are kept unchanged by lossless data hiding, the hidden data will be destroyed by outer processing. To address this issue, a lossless data hiding method called random element substitution (RES) is proposed for the Paillier cryptosystem by substituting the to-be-hidden bits for the random element of a cipher value. Moreover, the RES method is combined with another preprocessing-free algorithm to generate two schemes for lossless data hiding in encrypted images. With either scheme, a processed image will be obtained after the encrypted image undergoes processing in the homomorphic encrypted domain. Besides retrieving a part of the hidden data without image decryption, the data hidden with the RES method can be extracted after decryption, even after some processing has been conducted on encrypted images. The experimental results show the efficacy and superior performance of the proposed schemes.

With the growth of public demand for online access to health services, many efforts have been devoted to personal health records (PHR) in cloud computing. It enables patients to manage their personal health information (PHI) in cloud servers, which greatly facilitates the collection, access and sharing of PHI. Since cloud servers are not fully trusted, it is desirable that the PHI can be encrypted for privacy protection before uploaded to the cloud. Besides the privacy of PHI, fine-grained and flexible search control is also strongly desired for a secure PHR system. In this paper, we firstly present attribute set based keyword search (ASBKS) which can realize fine-grained keyword search of encrypted PHR. Compared with the existing searchable encryption with access control, the proposed ASBKS can achieve more flexibility in user attributes organization and more efficiency in specifying policies. Furthermore, we present a hierarchical ASBKS scheme to improve scalability by extending ASBKS with a hierarchical structure of users. We implement our ASBKS scheme and the experimental results demonstrate that it is both efficient and flexible for encrypted PHR in cloud computing.

With the rapid development of Internet of Things (IoT) and cloud computing, a large amount of IoT data has been stored and shared in cloud servers. However, sensitive IoT data may be leaked by untrusted cloud servers, which is a key problem hindering the development of IoT-cloud systems. To solve this problem, searchable encryption has been presented, which enables IoT devices to encrypt the collected data before uploading them to the cloud and make retrievals over the encrypted data by keyword queries. In this paper, we will study attribute-based keyword search (ABKS), which relieves us from cumbersome key management and provides a fine-grained access control. However, since the existing ABKS schemes are all constructed by bilinear pairings, which incurs high computational costs, they are not suitable for resource-constrained IoT devices. In this article, we propose an online/offline attribute-based boolean keyword search scheme, which can significantly reduce the online computing costs of IoT devices. In addition, our scheme can support boolean keyword search for data users, which has more flexible keyword expressivity than the existing online/offline ABKS schemes. We simulate our scheme and the experimental results show that it is both efficient and practical for the real IoT-cloud systems.