A Scheme for Verification on Data Integrity in Mobile Multicloud Computing Environment

In order to verify the data integrity in mobile multicloud computing environment, a MMCDIV (mobile multicloud data integrity verification) scheme is proposed. First, the computability and nondegeneracy of verification can be obtained by adopting BLS (Boneh-Lynn-Shacham) short signature scheme. Second, communication overhead is reduced based on HVR (Homomorphic Verifiable Response) with random masking and sMHT (sequence-enforced Merkle hash tree) construction. Finally, considering the resource constraints of mobile devices, data integrity is verified by lightweight computing and low data transmission. The scheme improves shortage that mobile device communication and computing power are limited, it supports dynamic data operation in mobile multicloud environment, and data integrity can be verified without using direct source file block. Experimental results also demonstrate that this scheme can achieve a lower cost of computing and communications

A New Reversible Date-Hiding Algorithm for Encrypted Images

In order to effectively increase embedding capacity and completely extract the watermarking information in information hiding of encrypted images, a new reversible watermarking embedding algorithm based on rhombus prediction model and difference histogram shifting ideas is proposed. Firstly, the images are pretreated according to rhombus prediction model. Then, the watermarking information is embedded in encrypted images by effective combination of homomorphism encryption scheme and reversible watermarking techniques. Finally, the watermarking information is completely extracted and the images are recovered based on computed difference histogram from left to right and from top to bottom. So, the efficiency and reversibility are ensured when watermarking information is embedded in encrypted image. Experiment results show that the proposed algorithm is simple and easy to realize, the embedding capacity is effectively increased, watermarking information is completely reversible, and the image can be recovered with no distortion

Fuzzy-Based Privacy-Preserving Scheme of Low Consumption and High Effectiveness for IoTs: A Repeated Game Model

In the Internet of things (IoTs), data transmission via network coding is highly vulnerable to intra-generation and inter-generation pollution attacks. To mitigate such attacks, some resource-intensive privacy-preserving schemes have been adopted in the previous literature. In order to balance resource consumption and data-privacy-preserving issues, a novel fuzzy-based privacy-preserving scheme is proposed. Our scheme is constructed on a T-S fuzzy trust theory, and network coding data streams are routed in optimal clusters formulated by a designed repeated game model to defend against pollution attacks. In particular, the security of our scheme relies on the hardness of the discrete logarithm. Then, we prove that the designed repeated game model has a subgame-perfect Nash equilibrium, and the model can improve resource utilization efficiency under the condition of data security. Simulation results show that the running time of the proposed privacy-preserving scheme is less than 1 s and the remaining energy is higher than 4 J when the length of packets is greater than 400 and the number of iterations is 100. Therefore, our scheme has higher time and energy efficiency than those of previous studies. In addition, the effective trust cluster formulation scheme (ETCFS) can formulate an optimal cluster more quickly under a kind of camouflage attack