Existing High Efficiency Video Coding (HEVC) selective encryption algorithms only consider the encoding characteristics of syntax elements to keep format compliance, but ignore the semantic features of video content, which may lead to unnecessary computational and bit rate costs. To tackle this problem, we present a content-aware tunable selective encryption (CATSE) scheme for HEVC. First, a deep hashing network is adopted to retrieve groups of pictures (GOPs) containing sensitive objects. Then, the retrieved sensitive GOPs and the remaining insensitive ones are encrypted with different encryption strengths. For the former, multiple syntax elements are encrypted to ensure security, whereas for the latter, only a few bypass-coded syntax elements are encrypted to improve the encryption efficiency and reduce the bit rate overhead. The keystream sequence used is extracted from the time series of a new improved logistic map with complex dynamic behavior, which is generated by our proposed sine-modular chaotification model. Finally, a reversible steganography is applied to embed the flag bits of the GOP type into the encrypted bitstream, so that the decoder can distinguish the encrypted syntax elements that need to be decrypted in different GOPs. Experimental results indicate that the proposed HEVC CATSE scheme not only provides high encryption speed and low bit rate overhead, but also has superior encryption strength than other state-of-the-art HEVC selective encryption algorithms.

Existing selective encryption schemes for High Efficiency Video Coding (HEVC) only focus on the encoding characteristics of syntax elements in entropy coding and lack an understanding of the video content. Consequently, a large amount of unnecessary encryption operations are utilized to protect insensitive video frames, resulting in low encryption efficiency. In this article, we propose a content-aware selective encryption scheme for H.265/HEVC, which encrypts only the groups of pictures (GOPs) containing sensitive content and thus offers high efficiency. In our scheme, a deep hashing network is first adopted to retrieve video frames to determine the content-sensitive GOPs. Then, multiple prediction and residual syntax elements in sensitive GOPs are encrypted using a keystream sequence generated by the hyper-chaotic Lorenz system. In addition, the direct current coefficient of each \(4\times 4\) transform block is exchanged with a pseudo-randomly selected non-zero alternating current coefficient to further offer stronger visual distortion. Finally, the sign bits used for marking each GOP-type are reversibly embedded into the encrypted syntax elements to facilitate the decoder to distinguish the GOPs that need to be decrypted. Experimental results indicate that the proposed content-aware selective encryption scheme can efficiently protect sensitive content and is robust against all common attacks. Furthermore, it outperforms other state-of-the-art HEVC selective encryption algorithms in terms of security performance.

Existing H.265/HEVC selective encryption (SE) schemes do not take into account the semantic features of input videos, nor do they adjust the encryption syntax elements according to the sensitivity of video content, which greatly limits their applicability. In this paper, we propose a chaos-based tunable H.265/HEVC SE scheme with semantic understanding. First, a deep hashing network is employed to identify content-sensitive videos by analyzing the semantic features of video sequences. Then, the non-sensitive videos and the retrieved sensitive ones are encrypted with different encryption strengths, respectively. Specifically, for non-sensitive videos, seven syntax elements with bypass-coded bins are selected for encryption at a constant bit rate. Hence, the encrypted bitstream keeps exactly the same compression ratio. To provide heavier visual distortion for content-sensitive videos, the regular-coded bins of four syntax elements and the intra prediction mode (IPM) are encrypted based on their corresponding encoding characteristics as well. Additionally, the selected syntax elements are all masked using a keystream generated by a chaotic system to ensure real-time constraints. Experimental results demonstrate that our suggested scheme offers format compatibility and is secure against all common attacks. Meanwhile, it outperforms state-of-the-art SE schemes in terms of security strength. Furthermore, the proposed scheme can be flexibly used in a wide range of applications according to the user’s requirements for encryption strength and bit rate.