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Adaptive Hangul Steganography Based on Chaotic Encryption Technique

혼돈 암호화 기법에 기반한 적응된 한글 스테가노그래피

  • Ji, Seon-Su (Department of Computer Science and Engineering, Gangneung Wonju National University)
  • Received : 2020.04.24
  • Accepted : 2020.05.26
  • Published : 2020.06.30

Abstract

Steganography uses digital images as a medium for sending secret messages over insecure networks. There is also a least significant bit(LSB) that is a popular method of embedding secret messages in digital images. The goal of steganography is to securely and flawlessly transmit secret messages using stego media over a communication channel. There is a need for a method to improve resistance to reduce the risk of exposure to third parties. To safely hide secret messages, I propose new algorithms that go through crossing, encryption, chaos and concealment steps. After separating Hangul syllables into choseong, jungseong and jongseong, the bitwised message information is encrypted. After applying the logistic map, bitwised information is reconstructed using the position of the chaotic sequence. The secret message is inserted into the randomly selected RGB channel. PSNR and SSIM were used to confirm the effectiveness of the applied results. It was confirmed as 44.392(dB) and 0.9884, respectively.

스테가노그래피는 안전하지 않은 네트워크를 통해 비밀 메시지를 전송하는데 사용하는 매개체로 디지털 이미지를 사용한다. 또한 디지털 이미지에 비밀 메시지를 포함시키는 방법 중에서 많이 사용하는 최하위 비트(LSB)가 있다. 스테가 노그래피의 목표는 통신 채널을 통해 스테고 매체를 이용하여 비밀 메시지를 안전하고, 무결하게 전송하는 것이다. 제3자에게 노출의 위험성을 감소시키기 위해 저항성을 향상시키는 방법이 필요하다. 비밀 메시지를 안전하게 숨기기 위해 교차, 암호화, 혼돈, 은닉 단계를 거치는 새로운 알고리즘을 제안한다. 한글 음절을 초성, 중성, 종성으로 분리한 후 비트화된 메시지 정보를 암호화 한다. 로지스틱 맵을 적용한 후에 혼돈 시퀀스의 위치를 가지고 비트화된 정보를 재구성한다. 비밀 메시지는 임의 선택된 RGB 채널에 삽입한다. 적용된 결과의 효율성을 확인하기 위해 PSNR과 SSIM을 이용하였다. 각각 44.392(dB), 0.9884로 확인하였다.

Keywords

References

  1. L. Yu, Y. Zhao, R. Ni and T. Li, "Improved Adaptive LSB Steganography Based on Chaos and Genetic Algorithm", EURASIP Journal on Advances in Signal Processing, Vol. 2010, pp. 1-6, 2010.
  2. P. Ranawat and S. Khandelwal, "Chaos Image Encryption using Transposition and Pixel Shuffling", International Journal of Innovations in Engineering and Technology, Vol. 4, Issue 4, pp. 259-265, 2014.
  3. M. Prasad and K. L. Sudha, "Chaos Image Encryption using Pixel shuffling", CCSEA 2011, CS & IT 02, pp. 169-179, 2011.
  4. G. T. Talee, M. J. Jelmeran and S. J. Mohammed, "A New Approach for Chaotic Encrypted Data Hiding in Color Image", International Journal of Computer Applications, Vol. 86, No. 8, pp. 23-26, January 2014. https://doi.org/10.5120/15006-3233
  5. K. Tutuncu and B. Demirci, "Adaptive LSB Steganography Based on Chaos Theory and Random Distortion", Advances in Electrical and Computer Engineering, Vol. 18, No. 3, pp. 15-22, 2018. https://doi.org/10.4316/AECE.2018.03003
  6. N. F. Elabady, H. M. Abdalkader, M. I. Moussa and S. F. Sabbeh, "Image Encryption Based on New One-Dimensional Chaotic Map", International Conference on Engineering and Technology(ICET), 2014.
  7. S. Rajendran and M. Doraipandian, "Chaotic Map Based Random Image Steganography using LSB Technique", International Journal of Network Security, Vol. 19, No. 4, pp. 593-598, July 2017.
  8. H. G. Kim and B. M. Kang, "Frequency Analysis of Hangul Usage", Korea Cultural Research Center, Korea University, 1997.
  9. Y. A. Y. Al-Najjar and D. C. Soong, "Comparison of Image Quality Assessment : PSNR, HVS, SSIM, UIQI", International Journal of Scientific & Engineering Research, Vol. 3, Issue 8, pp. 1-5, 2012.