Applications Transformation Model for MapReduce Information Hiding

With the popularity of smart mobile devices and the advancement of network and cloud computing technologies, it is unavoidable for traditional information hiding techniques applications, including digital watermarking, digital evidence and digital forensics, to face new challenges. Moreover, the International Data Corporation (IDC) report shows that the amounts of digital data will double every two years in the future, namely that the growth rate of multimedia is rapidly increasing. Therefore, the development of MapReduce information hiding applications transformation technique to deal with a huge amount of digital data would be a critical research issue. In this paper, Applications Transformation for MapReduce Information Hiding (AT-MIH) model is proposed to migrate information hiding applications into MapReduce framework and is proven by realizing an experimental system, a MapReduce-based Least Significant Bit (MR-LSB) as a case study. Experiments results show that the MR-LSB constructed by using AT-MIH model increases by a factor of 8.7X total execution time compared to traditional non-MapReduce method.