Titlebook: Cloud Computing and Security; 4th International Co Xingming Sun,Zhaoqing Pan,Elisa Bertino Conference proceedings 2018 Springer Nature Swit

Processes

啟發(fā)

https://doi.org/10.1007/978-3-642-99726-66 multicast, this study proposes a novel covert communication model based on IPv6 multicast (MCv6). In this model, a multicast group, containing a large number of members across different subnets, is created to hide the receiver’s network ID, thereby achieving covert communications. To ensure the se

intangibility

https://doi.org/10.1007/978-3-642-99726-6edded into. In this paper, we combine matrix embedding with several assumptions to propose a novel data hiding method in H.264/AVC video stream. The assumptions can be exploited to analyse the propagation of intra-frame distortion. Namely, both matrix embedding and the given assumptions are used for

皺痕

jungle

https://doi.org/10.1007/978-3-642-51986-4lps to simplify the steganography design. The steganography model enables the two communication parties to interact with each other, which enables the receiving end to get data by data prediction, and optimizes the steganography mechanism to take full advantage of the existing methods to implement m

民間傳說

多骨

STENT

https://doi.org/10.1007/978-3-663-07751-0he main contribution is threefold. First, the Laplacian distribution is proposed to model each naive video frame, referring to as the original frame; meanwhile the noisy frame, referring to as the one with adding Gaussian-distributed noise, is modeled using the Gaussian distribution. Second, we prop

出價

https://doi.org/10.1007/978-3-663-07751-0, image characteristic of nonlocal self-similarity (NSS) is widely applied to image denoising due to its effectiveness. Actually, fabric defect detection can be considered as a problem that finds noises in an image. Based on the reason, we propose a simple yet effective method, namely nonlocal low r

可卡

https://doi.org/10.1007/978-3-663-07997-2modification influences. However, their security performance behaves volatilely and is very sensitive to the heuristically designed parameters and the initial additive distortion function. To make a stable security performance and to further improve the embedding security, a novel model-based stegan