Tips & Tricks
Information hiding in edge location of video using amalgamate fft and cubic spline 2
Like this document? Why not share!
Survey on information hiding techni...
Data hiding - metodologie e strumen...
by Marco Ferrigno
Revisiting Information Hiding - R...
by Klaus Ostermann
A Study of Various Steganographic T...
by parvez Sharaf
by Sidharth Mohapatra
Email sent successfully!
Show related SlideShares at end
Information hiding in edge location of video using amalgamate fft and cubic spline 2
Aug 21, 2013
Comment goes here.
12 hours ago
Are you sure you want to
Your message goes here
Be the first to comment
Be the first to like this
Number of Embeds
No notes for slide
Information hiding in edge location of video using amalgamate fft and cubic spline 2
1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 240 INFORMATION HIDING IN EDGE LOCATION OF VIDEO USING AMALGAMATE FFT AND CUBIC SPLINE 1 Dr. Hanaa M. A. Salman Computer Science Department, University of Technology, Baghdad ABSTRACT This paper presents the concealment of information based on the use videos as a cover to hide the existence of the secret message. The secret message is encrypted using RSA before being embedded in the cover video. This encrypted secret message is then embedded in predetermine locations using Lest Significant Bits (LSB), and real part of Fast Fourier Transform (FFT). Finally inverse Discrete Fourier Transform (IDFT) is applied. The locations are cubic spline control points which are derived from detection the edge upon using (prewitt and canny). These control points are dynamically changed with each video frame to reduce the possibility of statistically identifying the locations of the secret message bits, even if the original cover video is made available to the interceptor. The proposed method is evaluated in terms of the Average Peak Signal to Noise Ratio (APSNR), as well as the Average Mean Square Error (AMSE) measured between the original and steganography video. Results show minimal degradation of the steganography video for secret message. Keywords: Video steganography, Edge detection, FFT, Cubic spline, PSNR, AMSE 1. INTRODUCTION One of the most important challenges facing the process of sending and displaying the hidden information, especially in public places is the presence of the intruder. The intruder starts to processes such as Interruption, modification, fabrication and Interception. One of the solutions to this problem is to use steganography. Steganography is a process of hiding information in cover media, in a way to keep others from thinking that the information even exists. There are basically three types of steganography protocols used, these are: Pure Steganography, Secret Key Steganography, Public Key Steganography. Steganography is mad of three parties: sender, receiver, and communication channel. The sender performs the embedding process over the carrier by using the secret information and the key to generate the stego-carrier. The receiver performs the extraction process over the stego-carrier by using the key to extract the secret information. The channel, it INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (IJCET) ISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), pp. 240-247 © IAEME: www.iaeme.com/ijcet.asp Journal Impact Factor (2013): 6.1302 (Calculated by GISI) www.jifactor.com IJCET © I A E M E
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 241 provides secure communicating between parties. Steganography  was normally combined with cryptography to further add another layer of security. A video file is generally a collection of images and sounds. The great advantages of video are the large amount of data that can be hidden inside and the fact that it is a moving stream of images and sounds. Therefore, any small but otherwise notice able distortions might go by unobserved by humans because of the continuous flow of information .Video steganography methods are broadly classified into (temporal domain and spatial domain), or (compressed video, and uncompressed video). Several researchers have addressed the problem of video steganography. In  a comparative analysis between Picture (JPEG) steganography and Video (AVI) steganography by quality and size was performed. The authors propose to increase the strength of the key by using UTF-32 encoding in the swapping algorithm and lossless steganoraphic technique in the AVI file. However, payload capacity is low. In  an adaptive invertible information hiding method for Moving Picture Expert Group (MPEG) video is proposed. Hidden data can be recovered without requiring the destination to have a prior copy of the covert video and the original MPEG video data can be recovered if needed. This technique works in frequency domain only. It has the advantages of low complexity and low visual distortion for covert communication applications. However, it suffers from low payload capacity. In, presents a steganoraphic model which utilizes cover video files to conceal the presence of other sensitive data regardless of its format. The model presented is based on pixel-wise manipulation of colored raw video files to embed the secret data. The secret message is segmented into blocks prior to being embedded in the cover video. These blocks are then embedded in pseudo random locations. The locations are derived from a re-orderings of a mutually agreed upon secret key. Furthermore, the re-ordering is dynamically changed with each video frame to reduce the possibility of statistically identifying the locations of the secret message blocks, even if the original cover video is made available to the interceptor. The author also presents a quantitative evaluation of the model using four types of secret data. The model is evaluated in terms of both the average reduction in Peak Signal to Noise Ratio (PSNR) compared to the original cover video; as well as the Mean Square Error (MSE) measured between the original and steganoraphic files averaged over all video frames. Results show minimal degradation of the steganoraphic video file for all types of data, and for various sizes of the secret messages. Finally, an estimate of the embedding capacity of a video file is presented In  authors search how the edges of the images can be used to hiding text message in gray image. The authors tried to give the depth view of image steganography and Edge detection Filter techniques. In  authors proposed a new technique using the motion vector, to hide the data in the moving objects. Moreover, to enhance the security of the data, the data is encrypted by using the AES algorithm and then hided. The data is hided in the horizontal and the vertical components of the moving objects. The PSNR value is calculated so that the quality of the video after the data hiding is evaluated. In  authors describe how motion vector can be used as a carrier to hide data. The secret message bit stream is first encrypted by using RSA algorithm and the encrypted is embedded in the least significant bit by using Least Significant Bit and also use edge detection mechanism for selecting the pixel. The performance is calculated by using Peak to Signal Noise Ratio. The performance analysis shows that the algorithm ensures better security against attackers An amalgamate method of Parametric Spline and DFT for video steganography is applied, instead of embedding secret information in all over the selected frame of video, an edge detection is applied followed by a curve selection method is applied as positions where, the secret bits to be
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 242 embedding. Thus if the intruder knows the set of control points it may lead to discover the secret message. An improvement is made by: 1. Extraction the intensity values of pixels for these control points along the frame of video. 2. Applying the DFT for the result intensity vector values. 3. Embedding information into the LSB's of the real part of DFT. 4. Apply IDFT. This paper is organized as follows: Section 2 introduces the proposed video based steganoraphic algorithm, and then presents the steps of embedding and extraction process. Section 3 presents the experimental results and finally, conclusions and future work are presented in section 4. 2. PROPOSED ALGORITHM The proposed video steganoraphic scheme is based on locations of the cubic spline interpolation control points over the hybrid edge detection methods; the Prewitt and the Canny. This proposed method consist of embedding phase as presented in section 3.1, and extraction phase as presented in section 3.2 3.1 EMBEDING PHASE The input to this phase is: secret message, video as cove media, and RSA public key of the receiver, while the output is the stego video. The block diagram of the embedding phase is shown in Figure (1), and the algorithm consists of the following steps described below. Step1: Secret message processing: convert the secret message into digits using Table (1). Apply RSAencryption algorithm as in . Step2: Cover video processing: Split the cover video into a sequence of frames, each video frame dimension is H ×W Pixels. For each randomly selected frame convert into grayscale frame, then apply edge detection using (Prewitt and Canny) algorithm as in [8, 7, 9]. Apply cubic spline interpolation algorithm as in  over the generated edge. Find control points to the generated cubic spline curve. Determined pixels value that corresponding location of these control points over the input frame. Step3: Embed processing: While the extracted frame pixels is not empty get the extracted frame byte .While the hidden message bits, is not empty get a bit and assigned it to the first bit of the real part of the DFT of the frame byte. Apply the IDFT. End of while hidden message. End of while extracted frame byte. Step4: End. Table 1 Number corresponds to each Litter Litter Number Litter Number Litter Number Litter Number A 00 H 07 O 14 V 21 B 01 I 08 P 15 W 22 C 02 J 09 Q 16 X 23 D 03 K 10 R 17 Y 24 E 04 L 11 S 18 Z 25 F 05 M 12 T 19 - 26 G 06 N 13 U 20
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 243 Figure 1: Schematic block diagram for the embedding process 3.2 EXTRACTION PHASE The input to the extraction phase is the stego video, and RSA privet key of the receiver, while the output is the hidden secret message. The block diagram of the extraction processes is shown in Figure (2) and the algorithm consists of the following steps described below: Step1: Stego video preprocessing: split the stego video into a sequence of frames, each stego video frame dimension is H ×W Pixels. For each randomly selected frame convert into grayscale frame, then apply edge detection using (Prewitt and Canny) algorithm. Apply cubic spline interpolation algorithm over the generated edge. Find control points to the generated cubic spline curve. Step2: Extract processing: Extract the stegovideo frame pixels in which the interplant curve pass by. While the extracted stego video frame pixels are not empty, get the first bit of each byte. End of while. End of frames. Step3: Decrypted message processing: Combined each seven bits of the extracted bits into digital number. Apply RSAdecryption Algorithm as in .Convert the result digit of size two into character using Table (1). The result is the secret message. Step4: END. Stego Video Secret Message Public Key RSA Encryption Encrypted Message Cover Video Split into Frames Frame Canny Edge Detection RGB to Grayscale Prewitt Edge Detection Cubic Spline Control FFT LSB IFFT
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 244 Figure 2: Schematic block diagram for the extracting process 3. PERFORMANCE EVALUATION EXPERIMENTAL RESULTS Steganography depends on the availability of two parameters, namely; imperceptibility and capacity. The perceptual imperceptibility of the embedded information is measured by comparing the original video to its stego counterpart so that their visual differences, if any, can be determined. Additionally, as an objective measure, Average Peak Signal to Noise Ratio (APSNR) between the cover and stego video may be calculated. These parameters are given by : ,……………………….……… (1) Where and are the pixel values at row i and column j of the cover frame and stego frame respectively. The Average Mean Square Error (AMSE) is given by: ,……………..………………………….……. (2) Where N is the number of frames for each video Secret Message Cubic Spline Control Points LSB Extraction RSA Decryption RSA Secret Key Prewitt Edge Detection RGB to Grayscale Canny Edge Detection Frame Split Frames Stego Video
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 245 The Peak Signal to Noise Ratio (PSNR) defined as : ,………………………...………………… (3) Where L is the peak signal level (L = 255 for 8-bit gray scale frames). The Average Peak Signal to Noise Ratio (APSNR) is given by: ,…………………...……………………….. (4) Where N is the number of frames for each video The maximum capacity of cover video file is given by: ,…………………...…………………… (5) The proposed algorithm has been implemented using Matlab, and Visual Basic, as shown in Figure (3).For all tests contained in this paper, we used N = 256. The experiments were conducted on 4 Video to test the robustness of the proposed algorithm by imperceptibility. The Experimental results show high imperceptibility where there is no noticeable difference between the stego video and the original. Figure 3 the proposed method implementation
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 246 Table (2) shows the calculate AMSE, and APSNR value between the original video and stego video for applying the proposed method to four test video. Table 2 AMSE and APSNR Covervideo Resolution (W×H) Frame /sec. No.of frames Size(MB) Average PSNR Average MSE Video 1 288×352 15 167 48.4 71.61 0.31 Video 2 288×352 15 190 55.1 73.52 0.32 Video 3 288×352 15 190 55.1 72.29 0.29 Video 4 288×352 15 189 55.1 72.30 0.36 In all experiments, the APSNR is greater than 72dB and AMSE is below 0.30. Therefore experimental results show that the proposed method is effective. It maintains the quality of the video and no variation between the cover data and stego data that can be detected by the human vision system. 4. CONCLUSIONS AND FUTURE WORK We proposed a method to hide secret message inside the Video, in frequency domain and without the need to have the original Video at the extraction phase. The sender encrypts the secret message by the RSA public key of the recipient and then embedded it using LSB of the pixels that located by the edge method (prewitt and canny) over the original video frame specified by the control points of cubic spline interpolation method, after conversion it into DFT and then IDFT applied to the real part of DFT, where the secret message is embedded using LSB insertion method. This process is repeated for each selected frame of the cover video. The receiver extract the LSB of the pixels that located by the edge method (prewitt, and canny) over the stego video frame specified by the control points of cubic spline interpolation method. This process is repeated for each selected frame of the stego cover video until all the embedded bits are extracted. The receiver revel the encrypted secret message with his RSA secret key .The proposed method relies on a set of parameters of secrecy, making it more resistant to attack by intruders. From these parameters: RSA secret key, which is used to decrypt the encrypted secret message, the number of control points which is used for each cubic spline that correspond to each edge in each used frame. These parameters must be known to intruders to extract secret message from the stego video file even he know the proposed algorithm. Future directions are: the use of other ways to find the edges, the use of other interpolation methods, or the adoption of other places for embedding, the use of wavelet transform.
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 247 REFERENCES  Sheelu, BabitaAhuja, An Overview of Steganography, Journal of Computer Engineering, Volume 11, Issue 1, PP 15-19,Jun. 2013.  Ajit Singh Swati Malik,Securing Data by Using Cryptography with Steganography, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 5, PP 404-409, May 2013.  AyushiJuneja , Sunita , TarunAhuja, Dynamic Least Significant Bit (DLSB) Technique forVideo Steganography, International Journal of Computer Science & Management Studies, Vol. 13, Issue 05, PP 52-56, July 2013.  R.Kavitha and A. Murugan, "Lossless Steganography on AVI File using Swapping Algorithm", InternationalConference on Computational Intelligence and Multimedia Applications, pp. 83-88, Sivakasi-TamilNadu, Dec. 2007  Yueyun Shang, "A New Invertible Data Hiding in Compressed Videos or Images.", Third International Conference on Natural Computation (ICNC 2007), Vol. 4,PP.576-580, Haikou, Aug 2007.  Amr A. Hanafy, Gouda I. Salama and Yahya Z. Mohasseb, "A Secure Covert Communication Model Based on Video Steganography”, in Military Communications Conference, 2008. MILCOM. IEEE on 16-19 Nov. 2008.  NitinJain SachinMeshram ShikhaDubey, Image Steganography Using LSB and Edge Detection Technique, International Journal of Soft Computing & Engineering, Volume: 2; Issue: 3,PP. 217- ,2012.  P. Paulpandi, Dr. T. Meyyappan, Hiding Messages Using Motion Vector Technique in Video Steganography, International Journal of Engineering Trends and Technology, Volume3, Issue3, 2012,  P. SunithaKency Paul, P.FascaGilgy Mary, J. Dheeba, A Data Hiding scheme in motion vector of videos by LSB Substitution., International Journal of Science, Engineering and Technology Research (IJSETR) Volume 2, Issue 5, PP 1111-1118, May 2013.  Shao-Hua Hong, Lin Wang, Trieu-Kien Truong, Tsung-Ching Lin, Lung-Jen Wang: Novel Approaches to the Parametric Cubic-Spline Interpolation. IEEE Transactions on Image Processing, Volume 22, Issue 3, PP: 1233-1241,March 2013.  M. Nagaraju Naik and P. Rajesh Kumar, “Spectral Approach to Image Projection with Cubic B-Spline Interpolation”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 3, Issue 3, 2012, pp. 153 - 161, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472.  Sonali Patil, Kapil Tajane and Janhavi Sirdeshpande, “Analysing Secure Image Secret Sharing Schemes Based on Steganography”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 2, 2013, pp. 172 - 178, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.  Geetha C.R. and Dr.Puttamadappa C., “Modified Weighted Embedding Method for Image Steganography”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 4, Issue 3, 2013, pp. 154 - 161, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472.  Vismita Nagrale, Ganesh Zambre and Aamir Agwani, “Image Stegano-Cryptography Based on LSB Insertion & Symmetric Key Encryption”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 2, Issue 1, 2011, pp. 35 - 42, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472.
Email sent successfully..