The steganographic model based on game theory is improved. A hybrid steganography model that satisfies the Kerckhoffs Principle by combining the strategy adaptation of the game theory model and the content adaptation in the cover model is proposed. This model is used to design a high security steganography algorithm for H.264 video. The distortion function in UNIWARD algorithm is improved according to the H.264 video coding characteristics. The improved distortion function is used to generate the bias function under the game theory model and the embedding probability of each position in the cover is calculated. The new distortion function under the hybrid model is generated by combining the embedding probability of the cover position and the distortion cost function under the improved UNIWARD algorithm, and using it to embed information in the H.264 residual DCT coefficient block. The experiment proves that the algorithm has higher security than the UNIWARD algorithm. With the same analysis algorithm, the detection error rate is significantly improved compared to the UNIWARD algorithm. The algorithm has large embedding capacity and good invisibility. When fully embedded, the capacity reaches 1.9% or more, the visual effect does not change significantly, and the PSNR value decreases within 2db. After the secret message embedded information, the video bit rate is increased within 9%.

In light of the existing security vulnerabilities within IoT publish–subscribe systems, our study introduces an improved end-to-end encryption approach using conditional proxy re-encryption. This method not only overcomes limitations associated with the reliance on a trusted authority and the challenge of reliably revoking users in previous proxy re-encryption frameworks, but also strengthens data privacy against potential collusion between the broker and subscribers. Through our innovative encryption protocol, unauthorized re-encryption by brokers is effectively prevented, enhancing secure communication between publisher and subscriber. Implemented on HiveMQ, an open-source MQTT platform, our prototype system demonstrates significant enhancements. Comparison to the state-of-the-art end-to-end encryption work, encryption overhead of our scheme is comparable to it, and the decryption cost is approximately half of it. Moreover, our solution significantly improves overall security without compromising the asynchronous communication and decentralized authorization foundational to the publish–subscribe model.

Steganography is a popular research direction in the field of information security. Due to the widespread use of video media, video steganography has received much attention from the research community. Among video steganography, motion vector (MV)-based video steganography has become one of the critical concerns of researchers due to its large embedding capacity and high visual quality. In this article, we focus on the research of MV-based video steganography. Firstly, the basic principles and evaluation criteria for MV-based steganography are discussed. Secondly, according to the different technical characteristics, the MV-based steganography is divided into three categories: the traditional MV domain steganography, the code-based MV domain steganography, and the adaptive MV domain steganography based on the framework of minimizing embedding distortion. The advantages and possible improvement directions of the above representative methods are illustrated. And then, the MV-based video steganalysis is outlined according to different perspectives of feature extraction, which is conducive to the design of better steganography algorithms. Finally, five future research directions are presented, such as designing distortion functions based on multiple factors, embedding methods based on new video coding standards, deep learning-based MV steganography, multidomain embedding strategies, and moving the MV-based steganography from the laboratory into the real world.

With the increasing emphasis on security and privacy, video in the cloud sometimes needs to be stored and processed in an encrypted format. To facilitate the indexing and tampering detection of encrypted videos, data hiding is performed in encrypted videos. This paper proposes a novel separable scheme for encryption and reversible data hiding. In terms of encryption method, intra-prediction mode and motion vector difference are encrypted by XOR encryption, and quantized discrete cosine transform block is permutated based on logistic chaotic mapping. In terms of the reversible data hiding algorithm, difference expansion is applied in encrypted video for the first time in this paper. The encryption method and the data hiding algorithm are separable, and the embedded information can be accurately extracted in both encrypted video bitstream and decrypted video bitstream. The experimental results show that the proposed encryption method can resist sketch attack and has higher security than other schemes, keeping the bit rate unchanged. The embedding algorithm used in the proposed scheme can provide higher capacity in the video with lower quantization parameter and good visual quality of the labeled decrypted video, maintaining low bit rate variation. The video encryption and the reversible data hiding are separable and the scheme can be applied in more scenarios.

A video watermarking robust algorithm based SVD is proposed. In order to analyze both the spatial and temporal characters of video sequence, each frame of the video is transformed to wavelet domain by 2-D DWT, and then 1-D DCT is used along the temporal axis. Watermarks were embedded into the singular values (SVs) of the coefficient frames and in the extraction procedure watermarks can be detected without the original video or any other information of the original singular values. Experiments show that the watermarked frames are indistinguishable from the original frames subjectively and the algorithm bears desirable robustness on filtering, additive noise, lossy compression, rotation and synchronization attacks etc.

To address the challenges of video copyright protection and ensure the perfect recovery of original video, we propose a dual-domain watermarking scheme for digital video, inspired by Robust Reversible Watermarking (RRW) technology used in digital images. Our approach introduces a parameter optimization strategy that incrementally adjusts scheme parameters through attack simulation fitting, allowing for adaptive tuning of experimental parameters. In this scheme, the low-frequency Polar Harmonic Transform (PHT) moment is utilized as the embedding domain for robust watermarking, enhancing stability against simulation attacks while implementing the parameter optimization strategy. Through extensive attack simulations across various digital videos, we identify the optimal low-frequency PHT moment using adaptive normalization. Subsequently, the embedding parameters for robust watermarking are adaptively adjusted to maximize robustness. To address computational efficiency and practical requirements, the unnormalized high-frequency PHT moment is selected as the embedding domain for reversible watermarking. We optimize the traditional single-stage extended transform dithering modulation (STDM) to facilitate multi-stage embedding in the dual-domain watermarking process. In practice, the video embedded with a robust watermark serves as the candidate video. This candidate video undergoes simulation according to the parameter optimization strategy to balance robustness and embedding capacity, with adaptive determination of embedding strength. The reversible watermarking is formed by combining errors and other information, utilizing recursive coding technology to ensure reversibility without attacks. Comprehensive analyses of multiple performance indicators demonstrate that our scheme exhibits strong robustness against Common Signal Processing (CSP) and Geometric Deformation (GD) attacks, outperforming other advanced video watermarking algorithms under similar conditions of invisibility, reversibility, and embedding capacity. This underscores the effectiveness and feasibility of our attack simulation fitting strategy.