Secured reversible color image data hiding technique using image classifiers and Lempel-Ziv-welch image compression technique

  • Authors

    • Anitha Devi M.D
    • K.B. Shiva Kumar
  • Recent advancement in data transfer and networking techniques has put forward a considerable threat for secure data transfer. It is the sensitive information that flows via network fuels the engine of global economy. One of the main concerns in data communication is the ability to exchange information in a secured fashion and embed the information of interest in any multimedia carrier like audio, video and an image. The proposed work is an ideal modernistic novel approach for secured sensitive information communication over an encrypted color host image carrying exceptionally confidential data. Distortion less retrieval of both payload and host signal information from marked image is an appealing feature in scenarios like medical, Military and satellite applications. Reversibility not only assures zero error retrieval of sensitive information hidden and also perfect reconstruction of host medium information contents while safeguarding the confidentiality of secret information. Most popular and widely in use Advanced Encryption Standard(AES) stream cipher in Counter mode is used for encrypting the cover image content, by performing XOR operation over cover image information bits with key dependent pseudorandom bits. Signal Processing over the encrypted domain is one of the most demanding features for most of the privacy preserving applications like cloud computing and remote sensing. High Embedding capability is achieved through Lempel-Ziv-Welch (LZW) compression technique. High performance reversible data hiding technique is assured via public key modulation scheme. Two of the most powerful image classifiers Support Vector Machine (SVM) and K- Nearest neighbor (KNN) algorithms are used at the decoder end to distinguish between encrypted and non encrypted image blocks. Performance evaluation of image classifiers is done, considering their ability to accurately categorize image patches as encrypted and unencrypted using feature vectors. Features used for categorizing encrypted and unencrypted image blocks are variation of pixel intensity in all four directions, entropy, standard deviation and histogram plot of segmented image blocks. Proposed algorithm comes with a unique feature of simultaneous retrieval of both host image and payload information in an error free fashion with zero distortion. Proposed algorithm is proven more secured considering several security attacks as evaluation parameters. Few of Cryptanalysis and Steganalysis techniques considered to verify the security feature of proposed algorithm are Sample pair analysis (SPA), Number of changing pixel rate (NPCR), Unified averaged changed intensity (UACI) and Chi-square attack.

  • References

    1. [1] Jiantao Zho, Weiwei Sun, Li Dong, Xianming Liu, Oscar C. Au, and Yuan Yan Tang, “Secure Reversible Image Data Hiding over Encrypted Domain via Key Modulationâ€. IEEE Transactions on Circuits and Systems for Video Technology PP.441 – 452, 2016.

      [2] X. Zhang, “Reversible data hiding in encrypted image,†IEEE Signal Process. Lett., vol. 18, no. 4, pp. 255–258, Apr. 2011.

      [3] W. Hong, T.-S. Chen, and H.-Y. Wu, “An improved reversible data hiding in encrypted images using side match,†IEEE Signal Process. Lett. vol. 19, no. 4, pp. 199–202, Apr. 2012.

      [4] Soria-Lorente and S. Berres, “A Secure Steganographic Algorithm Based on Frequency Domain for the Transmission of Hidden Information†Security and Communication Networks Volume 2017 (2017), Article ID 5397082.

      [5] L. Velasco-Bautista, J. C. L´opez-Hern´andez, M. Nakano-Miyatake, and H. M. P´erez-Meana, “Steganography in a digital image in the DCT domain.

      [6] Mehmet Utku Celik, Gaurav Sharma, A. Murat Tekalp, “Lossless Generalized-LSB Data Embeddingâ€, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 14, NO. 2, FEBRUARY 2005.

      [7] Mehmet Utku Celik, Gaurav Sharma, A. Murat Tekalp, “Lossless Watermarking for Image Authentication: A New Framework and an implementationâ€, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 15, NO. 4, APRIL 2006.

      [8] W. Puech, M. Chaumont, and O. Strauss, “A Reversible data hiding method for encrypted images†Proc. SPIE, vol. 6819, pp. 1–9, Feb. 2008.

      [9] Yongjian Hu, Heung-Kyu Lee, and Jianwei Li, “DE-Based Reversible Data Hiding With Improved Overflow Location Mapâ€, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 19, NO. 2, FEBRUARY 2009.

      [10] Xinpeng Zhang, “Separable Reversible Data Hiding in Encrypted Image†IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 7, NO. 2, APRIL 2012.

      [11] Xinpeng Zhang, “Reversible Data Hiding With Optimal Value Transferâ€, IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 15, NO. 2, FEBRUARY 2013.

      [12] Xiaolong Li, Weiming Zhang, Xinlu Gui, and Bin Yang , “A Novel Reversible Data Hiding Scheme Based on Two-Dimensional Difference-Histogram Modificationâ€, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 8, NO. 7, JULY 2013.

      [13] K. Ma, W. Zhang, X. Zhao, N. Yu, and F. Li, “Reversible data hiding in encrypted images by reserving room before encryption,†IEEE Trans. Inf. Forensics Security, vol. 8, no. 3, pp. 553–562, Mar. 2013.

      [14] Z. Qian, X. Zhang, and S. Wang, “Reversible data hiding in encrypted JPEG bit stream,†IEEE Trans. Multimedia, vol. 16, no. 5, pp. 1486–1491, Aug. 2014.

      [15] Anitha Devi M.D and K. B. Shivakumar“Protection of Confidential Color Image Information Based on Reversible Data Hiding Technique (PCCIRT) IEEE International Conference on computing and Network communications (CoCoNet’15), Dec 2015 978-1-4673-7308-1/15 pp 742-747.

      [16] Anitha Devi M.D and K.B.Shivakumar “A Novel Secured Reversible Covert Communication over Encrypted Domain Using SVM Classifier†IEEE explorer, september, 2017

      [17] Yue Wu, Student Member, IEEE, Joseph P. Noonan, Life Member, IEEE, and Sos Agaian, Senior Member, IEEE“NPCR and UACI Randomness Tests for Image Encryptionâ€CYBER JOURNALS: MULTIDISCIPLINARY JOURNALS IN SCIENCE AND TECHNOLOGY, JOURNAL OF SELECTED AREAS IN TELECOMMUNICATIONS (JSAT), APRIL EDITION, 2011.

      [18] Sorina Dumitrescu, Xiaolin Wu and Zhe Wang “Detection of LSB Steganography via Sample Pair Analysis “IEEE explorer, 2003.

      [19] John Babu, Sridevi Rangu, Pradyusha Manogna “ A Survey on different feature extraction and classification techniques used in image steganalysis “ Journal of Information security, 2017,8,186-202 ISSN online:2153-1242.

      [20] Brindha Murugan , Ammasai Gounden Nanjappa Gounder “Image encryption scheme based on blockbased confusion and multiple levels of Diffusion IET Journals“ISSN 1751-9632

      [21] X. Li, B. Yang, and T. Zeng, “Efficient reversible watermarking based on adaptive prediction-error expansion and pixel selection,†IEEE TransImage Process., vol. 20, no. 12, pp. 3524–3533, Dec. 2011.

      [22] T. Bianchi, A. Piva, and M. Barni, “On the implementation of the discrete Fourier transform in the encrypted domain,†IEEE Trans. Inf.Forensics Security, vol. 4, no. 1, pp. 86–97, Mar. 2009.

      [23] Z. Erkin, T. Veugen, T. Toft, and R. Lagendijk, “Generating private recommendations efficiently using homomorphic encryption and data packing,†IEEE Trans. Inf. Forensics Security, vol. 7, no. 3, pp. 1053–1066, Jun. 2012.

      [24] B. Yang, C. Busch, and X. Niu, “Joint reversible data hiding and image encryption,†Proc. SPIE, vol. 7541, pp. 1–10, Jan. 2010.

      [25] F. Cayre, C. Fontaine, and T. Furon, “Watermarking security: Theory and practice,†IEEE Trans. Signal Process., vol. 53, no. 10, pp. 3976–3987, Oct. 2005.

      [26] M. Barni, P. Failla, R. Lazzeretti, A. Sadeghi, and T. Schneider, “Privacy-preserving ECG classification with branching programs and neural networks,†IEEE Trans. Inf. Forensics Security, vol. 6, no. 2, pp. 452–468, Jun. 2011.

  • Downloads

  • How to Cite

    M.D, A. D., & Kumar, K. S. (2018). Secured reversible color image data hiding technique using image classifiers and Lempel-Ziv-welch image compression technique. International Journal of Engineering & Technology, 7(4), 3521-3529.