Text-steganography plays an increasingly significant role in covert-communication on Internet. Compared with study on text-steganography, research on text-steganalysis is in its infancy. In this paper, we present a statistical analysis of a kind of word-shift text-steganography by using neighbor difference (length difference of two consecutive spaces). We classify nature PDF documents into two cases serving for our analysis and statistically model wordshift steganographic embedding situations. Our method can reliably detect existence of hidden information. Furthermore, it quantitatively gives estimated embedding rate. The high performance of our method is demonstrated by experiments. Our work will contribute to both text-steganalysis and text-steganography.
SummaryIn a data sharing group, each user can upload, modify, and access group files and a user is required to generate a new signature for the modified file after modification. There is a situation that two or more users modify the same file at almost the same time, which should be avoided as it gives rise to a signature conflict. However, the existing schemes do not take it into consideration. In this paper, we proposed a new mechanism SeShare for data storing based on blockchain to realize signature uniqueness, which solves the problem of generating signatures for the same file meanwhile by different group users. Specifically, we record every signature of a file in a blockchain in chronological order, and only one user is allowed to add new signature at the end of the blockchain when modification conflicts occur. On the other hand, to provide a secure data sharing service, SeShare introduces an efficient public auditing scheme for file integrity verification when a group user leaves the group. We also prove the security of the proposed scheme and evaluate the performance at the end of this paper. Our experimental results demonstrate the efficiency of public auditing for user leaving.
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