A Master-Slave Blockchain Paradigm and Application in Digital Rights Management

Upon flaws of current blockchain platforms of heavyweight, large capacity of ledger, and time-consuming of synchronization of data, in this paper, we proposed a new paradigm of master-slave blockchain scheme(MSB) for pervasive computing that suitable for general PC, mobile device such as smart phones or PADs to participants in the working of mining and verification, in which we separated traditional blockchain model in 2 layer defined as master node layer and a series of slavery agents layer, then we proposed 2 approaches for partially computing model(PCM) and non-computing of model(NCM) in the MSB blockchain, Finally large amounts of simulations manifest the proposed master-slave blockchain scheme is feasible, extendible and suitable for pervasive computing especially in the 5 G generation environment, and can apply in the DRM-related applications.

A Novel Universal Steganalysis Algorithm Based on the IQM and the SRM

The state-of-the-art universal steganalysis method,spatial rich model(SRM),and the steganalysis method using image quality metrics(IQM)are both based on image residuals,while they use 34671 and 10 features respectively.This paper proposes a novel steganalysis scheme that combines their advantages in two ways.First,filters used in the IQM are designed according to the models of the SRM owning to their strong abilities for detecting the content adaptive steganographic methods.In addition,a total variant(TV)filter is also used due to its good performance of preserving image edge properties during filtering.Second,due to each type of these filters having own advantages,the multiple filters are used simultaneously and the features extracted from their outputs are combined together.The whole steganalysis procedure is removing steganographic noise using those filters,then measuring the distances between images and their filtered version with the image quality metrics,and last feeding these metrics as features to build a steganalyzer using either an ensemble classifier or a support vector machine.The scheme can work in two modes,the single filter mode using 9 features,and the multi-filter mode using 639 features.We compared the performance of the proposed method,the SRM and the maxSRMd2.The maxSRMd2 is the improved version of the SRM.The simulated results show that the proposed method that worked in the multi-filter mode was about 10%more accurate than the SRM and maxSRMd2 when the data were globally normalized,and had similar performance with the SRM and maxSRMd2 when the data were locally normalized.

(k, n) halftone visual cryptography based on Shamir＇ s secret sharing

（k, n） halftone visual cryptography （HVC） is proposed based on Shamir＇ s secret sharing （HVCSSS）, and through this method a binary secret image can be hided into n halftone images, and the secret image can be revealed from any k halftone images. Firstly, using Shamir＇ s secret sharing, a binary secret image can be shared into n meaningless shares; secondly, hiding n shares into n halftone images through self-hiding method; and then n extracted shares can be obtained from n halftone images through self-decrypt method; finally, picking any k shares from n extracted shares, the secret image can be revealed by using Lagrange interpolation. The main contribution is that applying Shamir＇ s secret sharing to realize a （k, n） HVC, and this method neither requires code book nor suffers from pixel expansion. Experimental results show HVCSSS can realize a （k, n） HVC in gray-scale and color halftone images, and correct decoding rate （CDR） of revealed secret image can be guaranteed.