Recently proposed steganalysis methods based on the local optimality of motion vector prediction (MVP) indicate that the existing HEVC (high efficiency video coding) motion vector (MV) domain video steganography algorithms can disturb the optimality of MVP in advanced motion vector prediction (AMVP) technology. In order to improve the security of steganography algorithm, this paper proposes an MV domain steganography method in HEVC based on MVP’s index and motion vector difference (MVD). First, we analyze the conditions that need to be met for steganography to resist attacks from MVP’s optimality features and other traditional steganalysis features. Then, a distortion function for minimizing embedding distortion is designed, and an algorithm for secret message embedding and extraction in units of inter-frame is proposed. Experimental results show that the proposed algorithm can resist attacks based on the optimality of MVP and also has high security against other traditional steganalysis methods. In addition, the proposed algorithm has excellent performance in visual quality and coding efficiency, and can be applied to practical scenarios of video covert communication.

Genes have great significance for the prevention and treatment of some diseases. A vital consideration is the need to find a way to locate pathogenic genes by analyzing the genetic data obtained from different medical institutions while protecting the privacy of patients’ genetic data. In this paper, we present a secure scheme for locating disease-causing genes based on Multi-Key Homomorphic Encryption (MKHE), which reduces the risk of leaking genetic data. First, we combine MKHE with a frequency-based pathogenic gene location function. The medical institutions use MKHE to encrypt their genetic data. The cloud then homomorphically evaluates specific gene-locating circuits on the encrypted genetic data. Second, whereas most location circuits are designed only for locating monogenic diseases, we propose two location circuits (TH-intersection and Top-q) that can locate the disease-causing genes of polygenic diseases. Third, we construct a directed decryption protocol in which the users involved in the homomorphic evaluation can appoint a target user who can obtain the final decryption result. Our experimental results show that compared to the JWB+17 scheme published in the journal Science, our scheme can be used to diagnose polygenic diseases, and the participants only need to upload their encrypted genetic data once, which reduces the communication traffic by a few hundred-fold.