Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 2: EECSI 2015

Performance Analysis on Text Steganalysis Method Using A Computational Intelligence Approach

Roshidi Din (Universiti Utara Malaysia)
Shafiz Affendi Mohd Yusof (Universiti Utara Malaysia)
Angela Amphawan (Universiti Utara Malaysia)
Hanizan Shaker Hussain (Kolej Poly-Tech MARA)
Hanafizah Yaacob (Kolej Poly-Tech MARA)
Nazuha Jamaludin (Kolej Poly-Tech MARA)
Azman Samsudin (Universiti Sains Malaysia)



Article Info

Publish Date
25 Sep 2017

Abstract

In this paper, a critical view of the utilization ofcomputational intelligence approach from the text steganalysisperspective is presented. This paper proposes a formalization ofgenetic algorithm method in order to detect hidden message on ananalyzed text. Five metric parameters such as running time, fitnessvalue, average mean probability, variance probability, and standarddeviation probability were used to measure the detection performancebetween statistical methods and genetic algorithm methods.Experiments conducted using both methods showed that geneticalgorithm method performs much better than statistical method,especially in detecting short analyzed texts. Thus, the findings showedthat the genetic algorithm method on analyzed stego text is verypromising. For future work, several significant factors such as datasetenvironment, searching process and types of fitness values throughother intelligent methods of computational intelligence should beinvestigated.

Copyrights © 2015






Journal Info

Abbrev

EECSI

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, ...