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IJMLC 2020 Vol.10(4): 568-575 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2020.10.4.974

Secure Information Hiding Based on Random Similar Bit Mapping

Abdul Alif Zakaria and Norli Anida Abdullah

Abstract—The goal of cryptography is to maintain the secrecy of information while steganography aims to hide the information. A hybrid steganography and cryptography method was introduced to increase the security of data transmission. Random Similar Bit Mapping (RSBM) was proposed to hide a secret message without modifying the image and generates a Position File (PF) which stores the positions of a hidden message. PF is encrypted using Advanced Encryption Standard (AES) algorithm before being sent to the receiver. Two security measures were proposed to estimate the message location in PF based on Correct Position Finding (CPF) for message detection against a brute force attack. This paper compared related works using the proposed security measures to evaluate its security. From the CPF probability analysis, RSBM produced the lowest CPF probability results, while recording the highest CPF time complexity results in CPF time complexity analysis. In conclusion, RSBM ensured high data security which can be implemented in any information hiding application.

Index Terms—Cryptography, information hiding, probability analysis, steganography, time complexity analysis.

A. A. Zakaria is with the Department of Cryptography Development, CyberSecurity Malaysia, 63000 Selangor, Malaysia (e-mail: alif@cybersecurity.my).
N. A. Abdullah is with the Centre for Foundation Studies in Sciences, University of Malaya, 50603 Kuala Lumpur, Malaysia (e-mail: norlie@um.edu.my).

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Cite: Abdul Alif Zakaria and Norli Anida Abdullah, "Secure Information Hiding Based on Random Similar Bit Mapping," International Journal of Machine Learning and Computing vol. 10, no. 4, pp. 568-575, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net


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