Near-optimal solution to pair-wise LSB matching via an immune programming strategy

Huan Xu, Jianjun Wang, Hyoung Joong Kim

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)


In this paper, a novel steganographic method is proposed employing an immune programming strategy to find a near-optimal solution for the pair-wise least-significant-bit (LSB) matching scheme. The LSB matching method proposed by Mielikaien utilizes a binary function to reduce the number of changed pixel values. However, his method still has room for improvement. A tier-score system is proposed in this paper to assess the performance of different orders for LSB matching. An immune programming approach is adopted to search for a near-optimal solution among all the permutation orders. The proposed method can reduce the distortion of the stego image, improve the visual quality, and decrease the probability of detection. The experimental results show that the proposed method achieves better performance than Mielikainen's pair-wise LSB matching method in terms of distortion and survival probability against steganalysis.

Original languageEnglish
Pages (from-to)1201-1217
Number of pages17
JournalInformation Sciences
Issue number8
Publication statusPublished - 2010 Apr 15


  • Immune programming
  • Information hiding
  • LSB matching
  • Steganography

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence


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