Abstract
With the ubiquitous progress of information technology it is now possible to transfer multimedia information rapidly over the Internet. Significant growth of video data on the Internet insists the users towards video steganography as a popular choice for data hiding. Steganography algorithm must emphasis to improve the embedding efficiency, payload and robustness against the intruders. In this paper, we have addressed those issues and present a new approach of steganography. Our segmentation process is based on video frames. We apply a region selection method followed by the dimensionality reduction process, called principal component analysis (PCA), to compress the regions and embed secret data on those compact regions. This PCA is used as a best-fitted vector that minimizes the average square distance from the pixel values to that vector. Our results show higher embedding capacity along with better visual quality. Moreover, the proposed method improves the robustness in the sense that the secret message can be retrieved by the receiver even after some known attacks on the channel.
Similar content being viewed by others
Notes
The error in the channel is govourned by some stastistical distribution
Abbreviations
- BER:
-
Bit Error Rate
- CR:
-
Compression ratio
- DCT:
-
Discrete cosine transform
- DWT:
-
Discrete wavelet transform
- LSB:
-
Least significant bit
- MAE:
-
Mean absolute error
- MOT:
-
Multiple object tracking algorithm
- MPE:
-
Mean percentage error
- MSE:
-
Mean Square Error
- PCA:
-
Principal component analysis
- PSNR:
-
Peak signal-to-noise ratio
- SF:
-
Similarity function
References
Al-Juaid NA, Gutub AA, Khan EA (2018) Enhancing PC data security via combining RSA cryptography and video based steganography. J Inform Secur Cybercrimes Res 1(1). https://doi.org/10.26735/16587790.2018.006
Alavianmehr MA, Rezaei M, Helfroush MS, Tashk A (2012). A lossless data hiding scheme on video raw data robust against H.264/AVC compression, 2nd International eConference on Computer and Knowledge Engineering (ICCKE), Mashhad, 194-198, https://doi.org/10.1109/ICCKE.2012.6395377
Cetin O, Akar F, Ozcerit AT, Cakiroglu M, Bayilmis C (2012) A blind steganography method based on histograms on video files. Imaging Sci J 60(2):75–82. https://doi.org/10.1179/1743131X11Y.0000000004
Chang PC, Chung KL, Chen JJ, Lin CH, Lin TJ (2014) A DCT/DST-based error propagation-free data hiding algorithm for HEVC intra-coded frames. J Visual Commun Image Representation 25(2):239–253. https://doi.org/10.1016/j.jvcir.2013.10.007
Cheddad A, Condell J, Curran K, Kevitt PM (2008) Enhancing steganography in digital images. Canadian Conf Comput Robot Vision, 326–332. https://doi.org/10.1109/CRV.2008.54
Dasgupta K, Mondal J, Dutta P (2013) Optimized video steganography using genetic algorithm (GA). Procedia Technology 10:131–137. https://doi.org/10.1016/j.protcy.2013.12.345
Ferryman J, Shahrokni A (2009) PETS2009: Dataset And challenge, Twelfth IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, Snowbird, UT, USA, 2009 1–6. https://doi.org/10.1109/PETS-WINTER.2009.5399556
Kar N, Mandal K, Bhattacharya B (2018) Improved chaos-based video steganography using DNA alphabets. ICT Express 4(1):6–13. https://doi.org/10.1016/j.icte.2018.01.003. ISSN 2405-9595
Mstafa RJ, Elleithy KM (2016) A video steganography algorithm based on Kanade-Lucas-Tomasi tracking algorithm and error correcting codes. Multimed Tools Appl 75:10311–10333. https://doi.org/10.1007/s11042-015-3060-0
Mstafa RJ, Elleithy KM (2017) Compressed and raw video steganography techniques: a comprehensive survey and analysis. Multimed Tools Appl 76:21749–21786. https://doi.org/10.1007/s11042-016-4055-1
Mstafa RJ, Elleithy KM, Abdelfattah E (2017) A Robust and Secure Video Steganography Method in DWT-DCT Domains Based on Multiple Object Tracking and ECC. IEEE Access 5:5354–5365. https://doi.org/10.1109/ACCESS.2017.2691581
Mukherjee S, Sanyal G (2017) Enhanced Position Power First Mapping (PPFM) based Image Steganography. Int J Comput Appl (IJCA), Taylor Francis 39(2):59–68. https://doi.org/10.1080/1206212X.2016.1273624
Mukherjee S, Sanyal G (2017) Enhanced Position Power First Mapping (PPFM) based image steganography. Int J Comput Appl 39(2):59–68. https://doi.org/10.1080/1206212X.2016.1273624
Mukherjee S, Sanyal G (2018) A chaos based image steganographic system. Multimed Tools Appl, Springer 77(21):27851–27876. https://doi.org/10.1007/s11042-018-5996-3
Mukherjee S, Sanyal G (2018) A multi level image steganography methodology based on adaptive PMS and block based pixel swapping. Multimed Tools Appl 78(13):17607–17622. https://doi.org/10.1007/s11042-018-7127-6
Mukherjee S, Sanyal G (2019) Edge based image steganography with variable threshold. Multimed Tools Appl 78:16363–16388. https://doi.org/10.1007/s11042-018-6975-4
Ntalianis K, Doulamis ND, Doulamis AD, Kollias SD (2002) An automatic video-object based steganographic system for multi-use message hiding using wavelet transform. IEEE International Conference on Systems Man and Cybernetics 3:6–12. https://doi.org/10.1109/ICSMC.2002.1176068
Ntalianis K, Tsapatsoulis N (2016) Remote authentication via biometrics: a robust Video-Object steganographic mechanism over wireless networks. IEEE Trans Emerg Topics Comput 4(1):156–174. https://doi.org/10.1109/TETC.2015.2400135
RR, DG, SS (2021) Efficient and secure data hiding in video sequence with three layer security: an approach using chaos. Multimed Tools Appl 80:13865–13878. https://doi.org/10.1007/s11042-020-10324-7
Roy S, Mukherjee S, Sanyal G (2018) Video Steganography Using karhunen-loève Transform. In: Proceedings of the 2nd International Conference on Digital Signal Processing, Tokyo Japan. https://doi.org/10.1145/3193025.3193045, pp 142–146
Roy S, Sanyal G (2016) An approach to selective encryption on compressed image 2nd International Conference on Contemporary Computing and Informatics (IC3I), Noida, 209-214, https://doi.org/10.1109/IC3I.2016.7917962
Sadek MM, Khalifa AS, Mostafa MGM (2015) Video steganography: A comprehensive review. Multimed Tools Appl 74:7063–7094. https://doi.org/10.1007/s11042-014-1952-z
Sadek MM, Khalifa AS, Mostafa MGM (2017) Robust video steganography algorithm using adaptive skin-tone detection. Multimed Tools Appl 76:3065–3085. https://doi.org/10.1007/s11042-015-3170-8
Schottle P, Böhme R (2016) Game Theory and Adaptive Steganography. IEEE Trans Inform Forens Secur 11(4):760–773. https://doi.org/10.1109/TIFS.2015.2509941
Shahid Z, Chaumont M, Puech W (2013) Considering the reconstruction loop for data hiding of intra- and inter-frames of h.264/AVC. SIViP 7:75–93. https://doi.org/10.1007/s11760-011-0225-9
Song G, Li Z, Zhao J, Hu J, Tu H (2015) A reversible video steganography algorithm for MVC based on motion vector. Multimed Tools Appl 74:3759–3782. https://doi.org/10.1007/s11042-013-1798-9
Sur A, Madhav Krishna SV, Sahu N, Rana S (2015) Detection of motion vector based video steganography. Multimed Tools Appl 74:10479–10494. https://doi.org/10.1007/s11042-014-2181-1
Weng X, Li Y, Chi L, Mu Y (2019) High-Capacity Convolutional video steganography with temporal residual modeling, international conference on multimedia retrieval (ICMR ’19), association for computing machinery, new york, NY, USA, 87–95. https://doi.org/10.1145/3323873.3325011
Wu K, Wang C (2015) Steganography Using Reversible Texture Synthesis. IEEE Trans Image Process 24(1):130–139. https://doi.org/10.1109/TIP.2014.2371246
Yao Y, Zhang W, Yu N, Zhao X (2015) Defining embedding distortion for motion vector-based video steganography. Multimed Tools Appl 74:11163–11186. https://doi.org/10.1007/s11042-014-2223-8
Zaitoun NM, Musbah J, Aqel MJ (2015) Survey on image segmentation techniques. Procedia Comput Sci 65:797–806. https://doi.org/10.1016/j.procs.2015.09.027
Zhang Y, Zhang M, Yang X, Guo D, Liu L (2017) Novel video steganography algorithm based on secret sharing and error-correcting code for h.264/AVC. Tsinghua Sci Technol 22(2):198–209. https://doi.org/10.23919/TST.2017.7889641
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Roy, S., Howlader, J. & Sanyal, G. A novel approach of data hiding in video using region selection and PCA. Multimed Tools Appl 81, 14553–14571 (2022). https://doi.org/10.1007/s11042-022-12029-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-022-12029-5