Sample PPT PhD thesis presentation 1.pptx

shekhartiwari207 2 views 41 slides Sep 17, 2025
Slide 1
Slide 1 of 41
Slide 1
1
Slide 2
2
Slide 3
3
Slide 4
4
Slide 5
5
Slide 6
6
Slide 7
7
Slide 8
8
Slide 9
9
Slide 10
10
Slide 11
11
Slide 12
12
Slide 13
13
Slide 14
14
Slide 15
15
Slide 16
16
Slide 17
17
Slide 18
18
Slide 19
19
Slide 20
20
Slide 21
21
Slide 22
22
Slide 23
23
Slide 24
24
Slide 25
25
Slide 26
26
Slide 27
27
Slide 28
28
Slide 29
29
Slide 30
30
Slide 31
31
Slide 32
32
Slide 33
33
Slide 34
34
Slide 35
35
Slide 36
36
Slide 37
37
Slide 38
38
Slide 39
39
Slide 40
40
Slide 41
41

About This Presentation

very good


Slide Content

“ Title of Thesis ” College Name , University Name PhD Scholar : Name of Scholar Supervisor : Dr. Sanjive Tyagi 1 Pre-submission Seminar Logo

Pre-submission Seminar Outline Conceptual Framework Introduction Literature Review Research Gap Research Objectives Scope of Study Motivation of Research Study A novel PDF Steganography Optimized Using Segmentation Technique A High Capacity PDF Text Steganography Technique Based On Hashing Using Quadratic Probing Steganography Model – Developed High Capacity Steganography Protected using Shamir’s threshold scheme and Permutation Framework Data Hiding Tool Based on PVD: SteganoPixTrans Conclusions and Future Scopes Research Paper Published References 2

Introduction (Explain your work by figure, This Sample) 3 Conceptual framework of steganography system

Steganographic model 4 . Introduction (cont.)

Literature reviewed (cont.) 5

Research Gap (cont.) Alteration takes place in cover text that prompts high probability of steganalysis attack. Embedding data and extracting data are not exactly similar. There are chances of errors during the extraction process. Embedding Huffman table of frequency in cover object increases the size of cover object file ( Lee & Tsai). Text media as cover object in steganography has not been touched much ( Johnson & Sallee ). 6

Research Gap Utilizing lower quality BMP file as cover image is drawback of Steganography technique. This is one of the major constraint (El- Emam N. N.). High Embedding capacity but not robust ( Fridrich et al .). Image steganography utilizing grayed image do not provide reasonable outcomes for higher embedding capacity when it is compared with 24 bits pixel RGB image. No satisfactory results of for higher security ( Wu & Tsai) . Cover-object manipulation that happened coincidentally during embedding process ( Katzenbeisser et al .,). Do not provide satisfactory result for large secret data and no special attention is given to strong security layers. 7

Problem Statement Text media in steganography to the lower side where as image steganography need to improve with three best feature together that are robustness, payload, and security. During steganography s pecific attention is not given to security and no appropriate encryption concept is being used. Layer of s ecurity to secret information is an issue of steganography. LSB based image steganography with limitation of BMP (Bitmap) as a cover object which generates lower quality BMP file whereas LSB steganography is the most common steganography that prompts to steganalysis attack. 8

Problem Statement Concentration on transmitting a high payload of secret data but not robust. Robustness is an issue of steganography. Grayed image as a cover object which provides lower embedding capacity in comparison to PVD scheme with an image of RGB 24 bits pixels . Cover-object manipulation that happens unexpectedly during the embedding process, which is not allowed in robust steganography. The recovery of extracted data accurately is an issue. 9

State of Art Steganography Implementation of extra ordinary secured layer like Shamir’s threshold scheme, Permutation Generator Algorithm associated with Distributed Secret Information Steganography (DSIS ). Proposed highly secured multilayer encryption technique using d-code, r-code, b-code and hashing with Quadratic Probing. Focused on a high quality image steganography with high embedding capacity utilizing novel PVD based steganography with 24 bits pixel of RGB image. Implementation of common pipeline (CP) for secret object like video, audio, image, text etc that comprises the ability to conceal any format of file which can be converted into Base64 format. 10

Research Objectives (cont.) To construct PDF text steganography techniques includes the features like highly secured steganography with multi-layered encryption scheme , no alteration in cover object , varying embedding capacity range from low level to high level , concept of reducing the size of stego -object without using compression approach and proper synchronization of encoding and decoding phase . To develop the image steganography algorithms comprises the features like high embedding capacity having exceptional high security layers , payload optimization using Genetic Algorithm , no distortion in visual quality of stego -image , and robustness by managing the synchronization . 11

Research Objectives To develop a software tool that measure and analyze the Security and Performance Issues of newly designed steganography algorithms . High security layers have to be implemented is the objective of study. 12

Scope of The Study The scope of study includes PDF steganography with high embedding capacity without impacting visual nature of cover PDF file and with no alteration in text of cover object. The scope of presented research work includes image steganography with high embedding capacity with exceptional high security to secret information by using an approach like Shamir’s threshold scheme (Highly secured mechanism) with robust steganographic system that maintains the synchronization between embedded and extracted data. The study includes multilayer security to secret information and dynamic multilevel embedding capacity from low volume payload to high volume payload. The study concentrates on Genetic Algorithm (GA) optimization that predict the dimension of secret-image and dimension of cover-image in advance for smooth and accurate execution of steganography process. 13

Scope of The Study Limitations : The primary focus of the presented research work has been concentrated on two type of steganography (1) Text steganography (2) Image steganography here limitations are mentioned. Limitation for Text steganography : In proposed text steganography cover file supports formats only PDF text file. Limitation for Image steganography : In proposed image steganography cover image supports formats like PNG, GIF, BMP and so on with lossless data compression format. It does not work with lossy compression like JPEG as cover object . 14

Trade-Off between Robustness, Imperceptibility, Payload, and Security 15 Motivation of Research Work (cont.)

A novel PDF Steganography Optimized Using Segmentation Technique Presented three novel scheme to obtain highly secured steganography technique by organizing the secrete bits within a segment of between-words spaces of cover PDF text (cases: m=1, m=2 or m=3 so on). Novel approach that no alteration takes place in the contents of the cover file by using ASCII code A0 in PDF File Authentication process of received stego -cover PDF file make it more stronger. 16

Experimental Results of Proposed Technique Introduced improved embedding capacity 2.142 % using high-frequency letters scheme that is higher than existing prominent technique (Text Steganography). Embedding capacity is improved by 36% by using high frequencies letters scheme 17

Outcome from Analysis Observation from the previous slides that if embedding capacity is increased from range 0.92% to 2.14% then quality of stego PDF file is not degraded e lse if it is increased to 3.36% then quality of stego PDF file is being degraded. Because as embedding capacity is increasing then Levenshtein distance percentage ( LDP) is decreasing, there by JWD will decrease from 1.00, which implies if embedding capacity will be increased beyond 2.14% that is 3.36% then visual quality of stego PDF text will be degraded in proposed scheme. 18

Objective Achieved M ultilayered security has been achieved successfully using decimal-code, remainder-code and binary-code a strong encryption scheme used in steganography. Successful steganalysis examination has proved that visual quality stego PDF file will not be degraded for acceptable embedding cases. Performance examination exhibits that the introduced steganographic system is protected . Thus , keeping in view the “trade-off” among robustness, payload, and security sufficient embedding capacity has been achieved. Here more attention is given to security than payload. 19

A High Capacity PDF Text Steganography Technique Based On Hashing Using Quadratic Probing 20

Training datasets used 21

Experimental O utcomes of the Proposed Scheme 22

Observing payloads based on selecting between-characters positions 23 73.21% Highest embedding capacity Varying Embedding Capacity is being achieved Proposed chosen case with 13.31% embedding capacity 1.66% Lowest embedding capacity

Comparative analysis of embedding c apacity of proposed approach with prominent existing approach Proposed chosen case with 13.31% embedding capacity Correlation or comparison of embedding capacity among existing and proposed method Scheme Utilized Embedding Capacity (%) Description (Agarwal, 2013) PA ( Paragraph _ Approach ) 2.151 Assessed by utilizing the dataset sample-2 in Table on previous slide ( Satir et al., 2012 ) 6.925 Assessed by utilizing the dataset sample 2 of mentioned article in Table on previous slide (Liu et al., 2011 ) 7.030 Assessed by utilizing the dataset sample-2 of mentioned article in Table on previous slide (Kumar et al., 2016 ) 7.210 Assessed by utilizing the dataset sample-2 of mentioned article in Table on previous slide (Agarwal, 2013) MLA _ (Missing Letter Approach) 8.672 Assessed by utilizing the dataset sample-2 in Table on previous slide ( Mahato et al., 2017 ) 9.100 Assessed by utilizing the sample in the mentioned articles (Malik et al., 2017 ) 10.891 Assessed by utilizing the dataset sample-1 of mentioned article in Table on previous slide Proposed approach 13.310 Assessed by utilizing the dataset sample-3 in Table on previous slide

Objective Achieved On comparing proposed approach with existing techniques (Agarwal, 2013; Kumar et al., 2016; Liu et al., 2011; Mahato et al., 2017; Satir et al., 2012), it is observed embedding capacity 13.31% of proposed approach better than various existing approaches . Keeping in view the trade-off between robustness, embedding capacity, and security is being achieved together . Successful steganalysis examination demonstrates that introduced approach is against steganalysis attacks shown by ROC curve Fascinating component of this strategy is that changeable embedding capacity could be achieved from 73.21% to 1.66 % . 25

High Capacity Steganography Protected using Shamir’s threshold scheme and Permutation Framework (cont.) 26

27 Comparison of ( ER) using existing image steganography (Chang et al., 2007; Ker, 2005; Zhang & Wang, 2004) and proposed with sample experimented image Comparative Analysis of ER

28 Comparison of PSNR using existing image steganography (Chang et al., 2007; Ker, 2005; Zhang & Wang, 2004) and proposed with sample experimented image Comparative Analysis of PSNR Proposed approach

Outcome from Analysis On comparing presented scheme with prominent existing PVD image steganographic schemes (Chang et al.; Ker; Zhang & Wang), it is observed embedding rate that BPP is 0.84 (average case of all chosen cases) improved than various mentioned existing approaches. It is also observed that (case 1) 1.50 BPP, (case 2) 0.75 BPP, (case 3) 0.75 BPP, (case 4) 0.38 BPP, a varying embedding rates are achieved by choosing changeable focused locations of (2x2) pixel square . WPSNRs are satisfactory as it lies above 60 which is adequately better WPSNR, SSIMs are satisfactory as it lies near to 1.0 which implies proposed algorithm accomplishes the prerequisite of imperceptibility . The PSNR value computed is 56.8154 db , it is adequately higher to fulfil our presented image steganography. 29

Objective Achieved Successful steganalysis examination of proposed steganography techniques using WPSNR, PSNR , SSIM, and histogram analysis demonstrates that introduced approach is strongly against steganalysis attack . One of the best a lgorithm for high embedding capacity by developing Distributed Secret Information Steganography-DSIS Multilayered High Security to secret information using Shamir’s Threshold Strategy Permutation Creator Scheme (PCS ). PVD based steganography Robustness - Keeping in view the trade-off between robustness, embedding capacity, and security, these three features are achieved together. High embedding capacity with adequate imperceptibility is successfully achieved. 30

Steganalysis Examination using Histogram Graph H istogram of the image is shown graphically with 256 number points on the horizontal axis i.e. X axis and their specific occurrences on the vertical axis i.e. Y axis . Histogram are drawn for cover image and stego image If histogram of cover image and stego image are exactly same then steganography is robust with high imperceptibility. If histogram of cover image and stego image are not exactly same then steganography is not robust and less imperceptibility It can be understand clearly from figure on next slide ( Navas et al .,) 31

Objective Achieved T he best cases (CASE 1 & CASE 3) are obtained on the basis of Capability Functions, steganalysis & embedding capacity by GA optimization. It demonstrates that presented steganography tool is more enhanced by GA Optimization technique so that we could be able found doubtful case in advance before starting the embedding process at large scale. Objective of achieving three best point (3BP) embedding capacity, robustness, and security together has accomplished. Here it is further concluded that proposed approach gives acceptable results to implement proposed software tool SteganoPixTrans in real time application. 32

Conclusions (cont.) 33 Technique # Robustness/ Undetectability & imperceptibility Security Level/Experimental results Payload/Best Cases 1 Anti Steganalysis by Similarity Metric: Jaro Winkler Ratio (1.00), Levenshtein distance (99.92). Highly satisfactory acceptable results Highly secured multilayer : using d-code, r-code & b-code. Robustness : special code A0 instead of bits (0 or 1) Highly secured results Highest in three schemes=1.58%, Highest by applying fourth scheme =2.142%, Acceptable payload better than various existing schemes 2 Anti Steganalysis & best case analysis by ROC curve with p ayload 13.31% & 18.31% are best case. Satisfactory acceptable results Encoding and decoding using hashing with QP (quadratic probing) Adequately secured results Highly improved from 1.66% to 73.21%, best case of embedding with robustness & high security =13.31% High Embedding Capacity

Conclusions 34 Chapter# Robustness/ Undetectability & imperceptibility Security Level/Experimental results Payload/Best Cases 3 Anti Steganalysis by WPSNR >60, SSIM near to 1.0, PSNR is 56.8154 db Adequate satisfactory acceptable results Highly secured multilayer : Shamir’s Threshold Scheme, Self synchronization by PCS used for distributing computing (DSIS) PVD based Steganography Highly secured results Highly improved bit rate 0.38 to 1.50 ( bpp ), & 1.48 to 5.87 (2x2) BPPB using distributing computing High Embedding Capacity 4 Anti- steganalysis : Using Histograms comparison, ROC curve analysis, PSNRs computation & analysis Highly satisfactory acceptable results CP for secret object like video, audio, image, text etc. & Cover image: lossless data compression like PNG, GIF, BMP etc. Anti- steganalysis examination shown highly secured. Quality real application software tool CASE 1 SSISF in range 5 kb to 257 kb & CASE 3 SSISF in range 182 kb to 257 kb. accepted. CASE 2 SSISF in range 258 kb to 386 kb rejected High quality results

Future Direction Proposed work implemented with H ighly secured framework like Shamir’s threshold scheme, Permutation Generator Algorithm, Distributed Secret Information Steganography (DSIS ) using image file as cover object and multilayer encryption technique using d-code, r-code, b-code and hashing with Quadratic Probing using PDF file as cover object. Implementation of proposed framework with video files as cover object would be interesting process. 35

Future Direction In presented image steganography cover image supports formats like PNG, GIF, BMP and so forth with lossless data compression format. So , one can implement it with lossy compression format like JPEG as cover object. Proposed study using a concept of packet switching of secret image across multiple images as carrier medium using DSIS, Shamir’s threshold scheme and Permutation Generator Algorithm For self-synchronization a concept of packet switching can also be implemented with intelligent coding scheme. 36

Future Direction For image steganography, there is still need to work to obtain similar special control code A0 as we have used in proposed PDF steganography . So , one may implement such cases in image steganography that should be image Steganography without embedding binary bits directly into cover image. The traditional image steganography technologies designate a cover image and embed secret data into it to form the stego -image. Need of image steganography that does not need to employ the designated cover image for embedding the secret data 37

Research Paper Published 38 Conference- 2016 Sanjive Tyagi , Ashendra Sexena and Sohan Garg . (2016). “ Secured High Capacity Steganography using Distribution Technique with Validity and Reliability” , In : Proc. of the International Conf. on SMART, IEEE conference, pp.109 – 114 , (UGC/Scopus Indexed). Publication- 2019 Sanjive Tyagi , Rakesh Kumar Dwivedi , Ashendra Kumar Saxena . (2019, May). “ A Novel PDF Steganography Optimized Using Segmentation Technique” , International Journal of Information Technology, https:// doi.org/10.1007/s41870-019-00309-7 , ISSN:2511-2112 Springer , ( UGC / Scopus Indexed ) . Sanjive Tyagi , Rakesh Kumar Dwivedi , Ashendra Kumar Saxena . (2019). “ A High Capacity PDF Text Steganography Technique Based on Hashing Using Quadratic Probing ”, International Journal of Intelligent Engineering and Systems, Vol.12 , No.3, pp. 192-202 , ISSN:2185-3118, ( UGC / Scopus Indexed ) .

References Abbas, C. J., Kevin, C., & Paul, M. K. (2010). Digital Image Steganography: Survey and Analysis of Current Methods. Signal Processing, vol. 90, no. 3, pp. 727-752. Agarwal M. (2013, January). Text Steganographic Approaches: A Comparison”, International Journal of Network Security & Its Applications (IJNSA), Vol.5, No.1, pp.91-106, DOI : 10.5121/ijnsa.2013.5107. Alizadeh , F., Canceill , N., Dabkiewicz , S. & Vandevenne , D. (2012, December). Using Steganography to Hide Messages Inside PDF Files. SSN Project Report. Chang, C.-C. & Hwang, R.-J. (2004). A New Scheme to Protect Confidential Images. Journal of Interconnection Networks, www.worldscientific.com, Vol. 5, No. 3, 221-232. Advanced Information Networking and Applications, 18th International Conference (IEEE), (Vol. 1) pp 158-163. Cheddad , A., Condell, J., Curran, K. & Mc Kevitt , P. (2007). A Comparative Analysis of Steganographic Tools. Proceedings of the Seventh IT&T Conference. Institute of Technology Blanchardstown , Dublin, Ireland, pp 29-37, 25th- 26th October 2007. Dasgupta K., Mandal , J.K., & Dutta , P. (2012, April). Hash Based Least Significant Bit Technique for Video Steganography (HLSB). International Journal of Security, Privacy and Trust Management (IJSPTM), Vol. 1(2), DOI:10.5121/ijsptm.2012.2201. Deshmukh , M., Nain, N. & Ahmed, M. (2017). A Novel Approach for Sharing Multiple Color Images by Employing Chinese Remainder Theorem. J. Vis. Commun . Image R. https://doi.org/10.1016/j.jvcir. 2017.09.013, 2017. Desoky , A. (2009). Notestega : Notes-Based Steganography Methodology. Information Security Journal: A Global Perspective, Vol. 18(4), pp. 178-193. El- Emam N. N. (2007). Hiding a Large Amount of Data with High Security Using Steganography Algorithm. Journal of Computer Science, 3 (4), 223-232. Faraoun , K. M. (2014, December). A Novel Fast and Provably Secure (T, N)-Threshold Secret Sharing Construction for Digital Images. Journal of Information Security And Applications, Vol 19(6), pp. 331-340, https://doi.org/10.1016/j.jisa.2014.10.013 Fendi , A., Wibisurya , A., & Faisal (2017). Distributed Steganography using Five Pixel Pair Differencing and Modulus Function. In proceedings of International Conference on Computer Science and Computational Intelligence, ICCSCI, Bali, Indonesia,116 (2017), pp. 334–341. Fridrich J., Goljan M. & Du R. (2001). Detecting LSB Steganography in Color and Grayscale Images, IEEE Multimedia (Multimedia and Security). Gongshen , L., Xiaoyun , D., Bo, S., & Kui , M. (2013). A Text Information Hiding Algorithm Based on Alternatives. Journal of Software, Vol. 8, No. 8, pp. 2072-2079. Hu, S. D. & Tak , U. K. (2011). A Novel Video Steganography Based on Non-uniform Rectangular Partition. IEEE: International Conference on Computational Science and Engineerin , pp.57-61, https://doi.org/10.1109/CSE.2011.24 Huang, C.-P. (2009). A New Scheme of Sharing Secrete in Stego Images with Authentication. ICIP 2009, 978-1-4244-5654-3/09 ©2009 IEEE. Jain, S., & Saxena , A. K. (2016). A Comparative Study of Various Security and Issues In Steganography Techniques. International Conference on Advanced Computing (ICAC-2016), pp. 35-44. Joshi, K., Gill, S., & Yadav , R. K. (2018). A New Method of Image Steganography Using 7th Bit of a Pixel as Indicator by Introducing the Successive Temporary Pixel in the Gray Scale Image. Journal of Computer Networks and Communications, Hindawi , Vol. 2018. Kanso , A. & Ghebleh , M. (2018). An Efficient Lossless Secret Sharing Scheme for Medical Images. Journal of Visual Communication and Image Representation, Vol. 56, pp. 245-255. Katzenbeisser , S. & Petitcolas , F. A. P. (2000). Information Hiding Techniques for Steganography and Digital Watermarking. Artech House, Inc. Norwood, MA, USA. Khairullah , Md. (2018, July). A Novel Steganography Method Using Transliteration of Bengali Text. Journal of King Saud University – Computer and Information Sciences, Vol.31, Issue 3, pp. 348-366, https://doi.org/10.1016/j.jksuci.2018.01.008. Khalil, M. I. (2011). Image Steganography: Hiding Short Audio Messages within Digital Images. Journal of Computer Science & Technology, vol. 11, no. 2, pp. 68-73. Ki-Hyun, J. & Kee -Young, Y. (2014). Data Hiding using Edge Detector for Scalable Images. Multimedia Tools and Applications, vol. 71, no. 3, pp. 1455-1468. Kipper, G. (2004). Investigator’s Guide to Steganography. Kodovsky J. & Fridrich J. (2008, January). Influence of Embedding Strategies on Security of Steganographic Methods in the JPEG Domain, Proc. SPIE Electronic Imaging, Security, Forensics, Steganography and Watermarking of Multimedia Contents X, 2 11-213, San Jose, CA. Kumar, R., Chand, S. & Singh, S. (2014). An Email Based High Capacity Text Steganography Scheme Using Combinatorial Compression. In: Proc. of the International Conf. on Confluence- The Next Generation Information Technology Summit, Noida, India, pp. 336–339. 39

References Kumar, R., Chand, S. & Singh, S. (2016). A High Capacity Email Based Text Steganography Scheme Using Huffman Compression. In: Proc. of the International Conf. on Signal Processing and Integrated Networks, Noida, India, pp. 53-56. Kumar, V., Bansal , A. & Muttoo , S. K. (2014). Data Hiding Method Based on Inter-Block Difference in Eight Queens Solutions and LSB Substitution. International Journal of Information Security and Privacy, (IGI Global), Vol. 8(2), pp. 55-68. Lai, Y.-C. & Tsai, W.-H. (2009). Covert Communication Via PDF Files by New Data Hiding Techniques. Department of Computer Science, National Chiao Tung University, Hsinchu , Taiwan, This work was supported by NSC project No. 97-2631- H-009-001, 2009. Lee I-S. & Tsai W.-H. (2010). A New Approach to Covert Communication via PDF Files. Signal Processing, Vol. 90, No. 2, pp. 557-565. Li, B., Wang, M., Li, X., Tan, S., & Huang, J. (2015, Sept.). A Strategy of Clustering Modification Directions in Spatial Image Steganography. in IEEE Transactions on Information Forensics and Security, vol. 10, no. 9, pp. 1905-1917, doi : 10.1109/TIFS.2015.2434600. Lingyun , X., Wenshuai , W., Xu , L., & Chunfang , Y. (2018). A Linguistic Steganography Based on Word Indexing Compression and Candidate Selection. Multimedia Tools And Applications, 77(21), pp 28969–28989. Liu, H., Li, L., Li, J., & Huang, J. (2011). Three Novel Algorithms for Hiding Data in PDF Files Based on Incremental Updates. https://link.springer.com/chapter/10.1007%2F978-3-642-32205-1_15. Mahato , S., Ali Khan, D., Yadav , D. K. (2017, February). A Modified Approach to Data Hiding In Microsoft Word Documents by Change-Tracking Technique. Journal of King Saud University - Computer and Information Sciences, Vol. 32(2), pp. 216-224, https://doi.org/10.1016/j.jksuci.2017.08.004. Malik, A., Sikka , G., & Verma , H. K. (2017, February). A High Capacity Text Steganography Scheme Based on LZW Compression and Color Coding. Engineering Science and Technology, an International Journal, Vol. 20(1),pp. 72-79, https://doi.org/10.1016/j.jestch.2016.06.005. Naqvi , N., Abbasi , A. T., Hussain , R. M., Khan, A., & Ahmad, B. (2018). Multilayer Partially Homomorphic Encryption Text Steganography (MLPHE-TS): A Zero Steganography Approach. Wireless Personal Communications, , 2018 [90], pp. 1-23. Rakesh , R., Devathi , S., Sekaran , P. S. C., & Kumar, S. S. (2011, May). Adaptive Randomization in Image Steganography Pertaining to Most Significant Nibble. International Journal of Computer Applications, Vol. 22(3). Ramana,K . V., Babu , B.R. & Babu , R. (2011, May). A Randomized Secure Data Hiding Algorithm Using File Hybridization for Information Security. International Journal on Computer Science and Engineering (IJCSE), Vol. 3 No. 5. Ramanpreet , K. & Singh, B. (2012). Survey and Analysis of Various Steganographic Techniques. International Journal of Engineering Science & Advanced Technology. vol. 2, no. 3, pp. 561-566. Ren , W., Liu,Y . & Zhao, J. (2012, June). Provably Secure Information Hiding via Short Text in Social Networking Tools. Tsinghua Science and Technology, ISSN 1007-0214 1/18 pp. 225-231, Vol. 17(3). . Satir , E. & Isik , H. (2012). A Compression-Based Text Steganography Method. Journal of Systems and Software, Vol. 85, No. 10, pp. 2385-239. Schonfeld , D. & Winker, A. (2007). Reducing the Complexity of Syndrome Coding for Embedding. In: Furon T., Cayre F., Doerr G., Bas P. ( eds ) Information Hiding. IH 2007, LNCS 4567, pp. 145-158. Sheisi , H., Mesgarian , J. & Rahmani , M. (2012, August). Steganography: Dct Coefficient Replacement Method and Compare with JSteg Algorithm. International Journal of Computer and Electrical Engineering, Vol. 4, No. 4, pp. 458-462. Shniperov , A. N. & Nikitina , K. A. (2016). A Text Steganography Method Based on Markov Chains. Automatic Control and Computer Sciences, Vol. 50, No. 8, pp. 802–808. Singh, P., & Raman, B. (2017). Reversible Data Hiding Based on Shamir’s Secret Sharing for Color Images over Cloud. Information Sciences. Vol 422, pp. 77-97. http://dx.doi.org/10.1016/j.ins.2017.08.077 Sloan, T. & Castro, J. H. (2018). Dismantling OpenPuff PDF Steganography. Digital Investigation, Vol. 25, pp. 90-96. Stephane G. R., Ekodeck , R. & Ndoundam (2016, August) . PDF Steganography Based on Chinese Remainder Theorem. Journal of Information Security and Applications, Vol. 29, pp. 1-15, https://doi.org/10.1016/j.jisa.2015.11.008. Wu, D.-C. & Tsai, W.-H. (2003). A Steganographic Method for Images by Pixel Value Differencing, Pattern Recognition Letters 24, pp. 1613–1626. Wua , X. & Yang, C.-N. (2019). A Combination of Color -Black-and-White Visual Cryptography and Polynomial Based Secret Image Sharing. Journal of Visual Communication and Image Representation, Vol. 61, pp.74-84. Yadav V. K. & Batham S. (2015). A Novel Approach of Bulk Data Hiding using Text Steganography. Procedia Computer Science, Vol. 57, pp. 1401-1410. Zhong , S., Cheng, X. & Chen, T. (2007, January). Data Hiding in a Kind of PDF Texts for Secret Communication. International Journal of Network Security, Vol.4 (1) pp.17-26 40

41