Increase of Capacity and Quality of Frequency Based Image Steganography Using Particle Swarm Optimization
Article No.: 4, Pages 1 - 5
Abstract
This paper proposes a steganography technique to enhance the capacity and quality of the stego object. The method is proposed for frequency domain grayscale images. It is assumed that hiding varied number of secret bits in the original image blocks depending upon the DCT coefficients remaining after quantizing the blocks might increase the capacity of the stego image. To enhance the quality PSO can be used to find the appropriate DCT coefficients to conceal the secret data. The secret message is to be encrypted using AES before embedding in the original image blocks to ensure security.
References
[1]
Almohamad, A., Ghinea, G. and Hierons, R. M. 2009. JPEG steganography: a performance evaluation of quantization tables. IEEE. 1550-445X/09. DOI=10.1109/AINA.2009.67
[2]
Bedi, P., Bansal, R. and Sehgal, P. 2013. Using PSO in a spatial domain based image hiding scheme with distortion tolerance. Elsevier Ltd. 24 Jan. 2013. DOI= http://dx.doi.org/10.1016/j.compeleceng.2012.12.021
[3]
Bhattacharya, D., Dutta, J., Das, P., Bandyopadhyay, S. K. and Kim, Tai-hoon. 2009. Discrete Cosine Transformation based Image Authentication and Secret Message Transmission scheme. IEEE. 978-0-7695-3743-6/09. DOI= 10.1109/CICSYN.2009.11
[4]
Blondin, J. 2009. Particle Swarm Optimization: A Tutorial. www.dmi.unict.it/mpavone/nc-cs/materiale/pso_tutorial.pdf
[5]
Cabeen, K. and Gent, P. Image Compression and the Discrete Cosine Transform. Math 45, College of the Redwoods
[6]
Chanu, Y. J., Tuithung, T. and Singh, K. M. 2012. A Short Survey on Image Steganography and Steganalysis Techniques. IEEE. 978-1-4577-0748-3/12
[7]
Fazli, S. and Kiamini, M. 2008. A High_Performance Steganographic Method using JPEG and PSO Algorithm. IEEE. 978-1-4244-2824-3/08
[8]
Kadam, P., Nawale, M., Kandhare, A. and Patil, M. 2013. Separable Reversible Encrypted Data Hiding in Encrypted Image Using AES algorithm and Lossy Technique. IEEE. 978-1-467-5848-3/13
[9]
Kaur, N. 2013. Steganography Using Particle Swarm Optimization- A Review. IJESRT. ISSN: 2277-9655. 3345--3347.
[10]
Prabhu, S. M., P. A., B. B., P. V. and P. S. 2015. Highly Secured Image Steganography Using Particle Swarm Optimization. IJETS. ISSN (P): 2349-3968, ISSN (O): 2349--3976, Vol. 2, Issue 3.
[11]
Rabevohitra, F. H. and Sang, J. 2011. Using PSO Algorithm for Simple LSB Substitution Based Steganography Scheme in DCT Transformation Domain. Springer. ICSI 2011, Part I, LNCS 6728, pp. 212--220.
[12]
Raja, K. B., Chowdary, C. R., Venugopal, K. R. and Patnaik, L. M. 2005. A Secure Image Steganography using LSB, DCT and Compression Techniques on Raw Images. IEEE. 0-7803-9588-3/05.
[13]
Saha, B. and Sharma, S. 2012. Steganographic Techniques of Data Hiding using Digital Images. DEF. SCI. J. Vol. 62, No. 1, pp. 11--18, DOI=10.14429/dsj.62.1436
[14]
Song, S., Zhang, J., Liao, X., Du, J. and Wen, Q. 2011. A Novel Secure Communication protocol Combining Steganography and Cryptography. Elsevier. pp. 2767--2772. DOI=10.1016/j.proeng.2011.08.521.
[15]
Thangadurai, K. and Sudha, G. 2014. An analysis of LSB Based Image Steganography Techniques. IEEE. 978-1-4799-2352-6/14.
[16]
Vanmathi, C., and Prabu, S. 2013. A Survey of State of the Art technique of Steganography. IJET. ISSN: 0975-4024. Vol 5, No 1.
[17]
Parekh, R. 2013. Principles of Multimedia, 2e. McGraw-Hill. ISBN (13): 978-1-25-900650-0.
[18]
Forouzan, B. A. 2013. Data Communications and Networking, Fourth Edition. McGraw-Hill. ISBN-13: 978-0-07-063414-5
[19]
Kachitvichyanukul, V. 2012. Comparison of Three Evolutionary Algorithms: GA, PSO and DE. KIIE. Vol II, No 3, September 2012, pp. 215--223. ISSN 1598-7248, EISSN 2234-6473. DOI= http://dx.doi.org/10.7232/iems.2012.11.3.215.
[20]
Li, X. and Wang, J. 2007. A steganographic method based upon JPEG and particle swarm optimization algorithm. Elsevier. pp. 3099--3109, DOI=10.1016/j.ins.2007.02.008
[21]
Varadi, D. 2013. Social Learning Algorithm: Particle Swarm Optimization (PSO). CSSA. https://cssanalytics.wordpress.com/2013/09/06/social-learning-algorithms-particle-swarm-optimization-pso/
- Increase of Capacity and Quality of Frequency Based Image Steganography Using Particle Swarm Optimization
Recommendations
A Novel n-Rightmost Bit Replacement Image Steganography Technique
Image steganography is a technique for hiding the secret data in a carrier image. This paper proposes a novel n-right most bit replacement image steganography technique to hide the secret data in an image, where 1?≤?n?≤?4. The major objectives of the ...
An adjustable-purpose image watermarking technique by particle swarm optimization
Imperceptibility, security, capacity, and robustness are among many aspects of image watermarking design. An ideal watermarking system should embed a large amount of information perfectly securely, but with no visible degradation to the host image. Many ...
Digital audio steganography using DWT with reduced embedding error and better extraction compared to DCT
ICWET '11: Proceedings of the International Conference & Workshop on Emerging Trends in TechnologyThe proposed system showed high hiding rates with reasonable imperceptibility compared to other steganographic systems, DCT and better audio quality. The results shown gives detail comparison between DWT and DCT. In this paper a novel method for digital ...
Comments
Information & Contributors
Information
Published In
March 2016
843 pages
ISBN:9781450339629
DOI:10.1145/2905055
Copyright © 2016 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 March 2016
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ICTCS '16
ICTCS '16: Second International Conference on Information and Communication Technology for Competitive Strategies
March 4 - 5, 2016
Udaipur, India
Acceptance Rates
Overall Acceptance Rate 97 of 270 submissions, 36%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 58Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 02 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in