With the popularity of image editing tools, the originality and information security of images are facing serious threats. The most common threat is splicing forgery that copies a part of the area from one donor image to the acceptor one. Some research works were proposed to protect the image originality, whereas they are still difficult to apply in practice. There are two main reasons: (a) very limited data for learning models; (b) huge attribute differences between the donor and acceptor images. We propose two novel tasks to conquer the above challenges: Synthetic Adversarial Networks (SANs) and Hybrid Dense U-Net (HDU-Net). SAN finds the most secluded position for inserting tampered areas in an image by learning the association between scenes and objects, and can enlarge the original small data set by more than 40 times. We call the data set SF-Data generated by SAN. We combine the dense U-Net that detects the differences of the essential attributes of image with four spaces containing more available feature information to propose HDU-Net. Then, the synthetic data set SF-Data are used to train HDU-Net. We perform various attack experiments on several public data sets to demonstrate the effectiveness and robustness of our method.

While cloud computing services such as cloud storage are fairly mature, it remains challenging to design efficient and secure cryptographic schemes to facilitate fine-grained access control and achieve other features. For example, existing ciphertext-policy attribute-based encryption schemes do not generally have in-place limits on the number of access or access duration, which can consequently be exploited to perform economic denial of sustainability and other attacks. In addition, improving system efficiency can be challenging in large-scale operations. Thus, in this paper, we present a blockchain-based access control with k $k$ -times tamper resistance. Our proposed approach allows one to set and enforce quota/limits on the number of accesses allowed for each user, whose integrity is ensured using blockchain. In addition, our proposed approach also allows multiple attribute authorities to coexist and work together with a central authority to facilitate secret key distribution and improve system efficiency. We then evaluate the security and the efficiency of our proposed approach to demonstrate its utility.