ISE: AN INTELLIGENT AND EFFICIENT STEGANALYSIS ENGINE FOR IMAGE DATABASE IN BIG DATA SYSTEMS
Journal Title: Azerbaijan Journal of High Performance Computing - Year 2018, Vol 1, Issue 1
Abstract
The aim of this work is to design a faster and artificially intelligent steganalysis engine, which is able to secure the image databases from any infected image in big data environment. The proposed Intelligent Steganalysis Engine (ISE) for image database in big data makes use of three steps, which are image estimation, feature generation and classification. In the first step, five new images are estimated from the original image, for computing 438 features and then these data images are passed through a classifier for final prediction of a stego image. The engine is designed based on Map-Reduce programming approach to cope with big data. The actual experiments were performed on the Big Data Hadoop by taking standard image data set. In the first two steps, the images are processed in both spatial and DCT domain. During these steps the implementations of image estimation and feature extraction algorithms become very much computationally intensive and seek a huge amount of time. The results obtained are compared with previously reported six similar works and an inference has been drawn for appropriate use of feature set and classifier pair.
Authors and Affiliations
Mayank Tiwary, Pritish Mishra, Mohammad S. Obaidat, Deepak Puthal
EXAMIG MATRIX: PROCESS MIGRATION BASED ON MATRIX DEFINITION OF SELECTING DESTINATION IN DISTRIBUTED EXASCALE ENVIRONMENTS
In traditional computing system, load balancer, interim selecting the process, determine the destination computing node based on describing Indicators process status. In distributed Exascale computing system, due to the...
A SURVEY OF RESOURCE MANAGEMENT CHALLENGES IN MULTI-CLOUD ENVIRONMENT: TAXONOMY AND EMPIRICAL ANALYSIS
HOME ABOUT SUBMISSION SEARCH CURRENT ARCHIVES A SURVEY OF RESOURCE MANAGEMENT CHALLENGES IN MULTI-CLOUD ENVIRONMENT: TAXONOMY AND EMPIRICAL ANALYSIS Hits: 159 PDF Volume 1 (1), July 2018, Pages 51-65 Bandar Aldawsari1,...
CONVERGENCE OF HPC AND AI: TWO DIRECTIONS OF CONNECTION PDF
This paper examines the role of HPC systems in the solution of the most AI problems, on the other hand, assesses the impact of the application of AI methods on the resolution of different tasks in distributed systems. Th...
MULTI-START JAYA ALGORITHM FOR SOFTWARE MODULE CLUSTERING PROBLEM
Jaya algorithm has gained considerable attention lately due to its simplicity and requiring no control parameters (i.e. parameter free). Despite its potential, Jaya algorithm is inherently designed for single objective p...
CHALLENGES OF RESOURCE DISCOVERY TO SUPPORT DISTRIBUTED EXASCALE COMPUTING ENVIRONMENT
The resource discovery management unit (RD) in distributed Exascale systems needs to be able to manage the occurrence of dynamic and interactive events in the requesting process when running activities related to RD. The...