CHRIST COLLEGE OF ENGINEERING AND TECHNOLOGY DEPARTMENT OF COMPUTER SCIENCE ENGINEERING AND TECHNOLOGY.

Slides:



Advertisements
Similar presentations
Low-Complexity Transform and Quantization in H.264/AVC
Advertisements

Capacity-Approaching Codes for Reversible Data Hiding Weiming Zhang, Biao Chen, and Nenghai Yu Department of Electrical Engineering & Information Science.
15 Data Compression Foundations of Computer Science ã Cengage Learning.
Data Compression CS 147 Minh Nguyen.
“Advanced Encryption Standard” & “Modes of Operation”
F5 A Steganographic Algorithm
SWE 423: Multimedia Systems
Department of Computer Engineering University of California at Santa Cruz Data Compression (3) Hai Tao.
JPEG.
Losslessy Compression of Multimedia Data Hao Jiang Computer Science Department Sept. 25, 2007.
1 An Efficient Mode Decision Algorithm for H.264/AVC Encoding Optimization IEEE TRANSACTION ON MULTIMEDIA Hanli Wang, Student Member, IEEE, Sam Kwong,
Lecture 23 Symmetric Encryption
5. 1 JPEG “ JPEG ” is Joint Photographic Experts Group. compresses pictures which don't have sharp changes e.g. landscape pictures. May lose some of the.
On Error Preserving Encryption Algorithms for Wireless Video Transmission Ali Saman Tosun and Wu-Chi Feng The Ohio State University Department of Computer.
1 JPEG Compression CSC361/661 Burg/Wong. 2 Fact about JPEG Compression JPEG stands for Joint Photographic Experts Group JPEG compression is used with.jpg.
Image Compression JPEG. Fact about JPEG Compression JPEG stands for Joint Photographic Experts Group JPEG compression is used with.jpg and can be embedded.
CSE679: MPEG r MPEG-1 r MPEG-2. MPEG r MPEG: Motion Pictures Experts Group r Standard for encoding videos/movies/motion pictures r Evolving set of standards.
Image and Video Compression
Image Compression - JPEG. Video Compression MPEG –Audio compression Lossy / perceptually lossless / lossless 3 layers Models based on speech generation.
Trevor McCasland Arch Kelley.  Goal: reduce the size of stored files and data while retaining all necessary perceptual information  Used to create an.
JPEG 2000 Image Type Image width and height: 1 to 2 32 – 1 Component depth: 1 to 32 bits Number of components: 1 to 255 Each component can have a different.
Digital Image Watermarking Er-Hsien Fu EE381K Student Presentation.
CS Spring 2012 CS 414 – Multimedia Systems Design Lecture 8 – JPEG Compression (Part 3) Klara Nahrstedt Spring 2012.
ECE472/572 - Lecture 12 Image Compression – Lossy Compression Techniques 11/10/11.
MPEG MPEG-VideoThis deals with the compression of video signals to about 1.5 Mbits/s; MPEG-AudioThis deals with the compression of digital audio signals.
Video Coding. Introduction Video Coding The objective of video coding is to compress moving images. The MPEG (Moving Picture Experts Group) and H.26X.
: Chapter 12: Image Compression 1 Montri Karnjanadecha ac.th/~montri Image Processing.
Klara Nahrstedt Spring 2011
IMAGE COMPRESSION USING BTC Presented By: Akash Agrawal Guided By: Prof.R.Welekar.
Concepts of Multimedia Processing and Transmission IT 481, Lecture 5 Dennis McCaughey, Ph.D. 19 February, 2007.
Digital Watermarking Sapinkumar Amin Guided By: Richard Sinn.
JPEG. The JPEG Standard JPEG is an image compression standard which was accepted as an international standard in  Developed by the Joint Photographic.
Indiana University Purdue University Fort Wayne Hongli Luo
CIS679: Multimedia Basics r Multimedia data type r Basic compression techniques.
JPEG CIS 658 Fall 2005.
Chapter 7 – End-to-End Data Two main topics Presentation formatting Compression We will go over the main issues in presentation formatting, but not much.
Hardware/Software Codesign Case Study : JPEG Compression.
Digital Image Processing Image Compression
A Novel steganographic method for JPEG images by Vasiliy Sachnev - Introduction  JPEG compression  Steganography - Block based steganography method (F5)
1 Image Formats. 2 Color representation An image = a collection of picture elements (pixels) Each pixel has a “color” Different types of pixels Binary.
Reversible hiding in DCT-based compressed images Authors:Chin-Chen Chang, Chia-Chen Lin, Chun-Sen Tseng and Wei-Liang Tai Adviser: Jui-Che Teng Speaker:
Introduction to Steganalysis Schemes Multimedia Security.
CS Spring 2014 CS 414 – Multimedia Systems Design Lecture 10 – Compression Basics and JPEG Compression (Part 4) Klara Nahrstedt Spring 2014.
Advances in digital image compression techniques Guojun Lu, Computer Communications, Vol. 16, No. 4, Apr, 1993, pp
Lecture 23 Symmetric Encryption
Performed by: Dor Kasif, Or Flisher Instructor: Rolf Hilgendorf Jpeg decompression algorithm implementation using HLS PDR presentation Winter Duration:
DATA & COMPUTER SECURITY (CSNB414) MODULE 3 MODERN SYMMETRIC ENCRYPTION.
Page 11/28/2016 CSE 40373/60373: Multimedia Systems Quantization  F(u, v) represents a DCT coefficient, Q(u, v) is a “quantization matrix” entry, and.
STATISTIC & INFORMATION THEORY (CSNB134) MODULE 11 COMPRESSION.
Introduction to JPEG m Akram Ben Ahmed
JPEG. Introduction JPEG (Joint Photographic Experts Group) Basic Concept Data compression is performed in the frequency domain. Low frequency components.
MPEG CODING PROCESS. Contents  What is MPEG Encoding?  Why MPEG Encoding?  Types of frames in MPEG 1  Layer of MPEG1 Video  MPEG 1 Intra frame Encoding.
By Dr. Hadi AL Saadi Lossy Compression. Source coding is based on changing of the original image content. Also called semantic-based coding High compression.
Submitted To-: Submitted By-: Mrs.Sushma Rani (HOD) Aashish Kr. Goyal (IT-7th) Deepak Soni (IT-8 th )
Cryptographic Hash Function. A hash function H accepts a variable-length block of data as input and produces a fixed-size hash value h = H(M). The principal.
H. 261 Video Compression Techniques 1. H.261  H.261: An earlier digital video compression standard, its principle of MC-based compression is retained.
 Digital images store large amounts of data and information. This data can be manipulated to some extend without being detected by human eyes.  DWT(Discrete.
JPEG Compression What is JPEG? Motivation
Source: IEEE Signal Processing Letters (Accepted)2016
IMAGE COMPRESSION.
Data Compression.
JPEG.
Data Compression CS 147 Minh Nguyen.
Reversible Data Hiding in JPEG Images using Ordered Embedding
Watermarking for Image Authentication ( Fragile Watermarking )
ENEE 631 Project Video Codec and Shot Segmentation
New Framework of Reversible Data Hiding in Encrypted JPEG Bitstreams
Image Coding and Compression
New Framework for Reversible Data Hiding in Encrypted Domain
Presentation transcript:

CHRIST COLLEGE OF ENGINEERING AND TECHNOLOGY DEPARTMENT OF COMPUTER SCIENCE ENGINEERING AND TECHNOLOGY

INFORMATION HIDING IN ENCRYPTED IMAGES AND VIDEOS PROJECT GUIDE MR.KISHORE ANTHUVAN SUBMITTED BY V.ASHWANTH B.HARISH A.JOHN PREM KUMAR

INDEX ABSTRACT. ABOUT THE DOMAIN. EXISTING SYSTEM. EXISTING SYSTEM DIAGRAM. PROPOSED SYSTEM. PROPOSED SYSTEM DIAGRAM. CLASSIFICATION OF MODULES. IMAGE AND DATA ENCRYPTION. DATA EMBEDDING AND COMPRESSION.

INDEX(CONTI….) SPLITING OF VIDEOS AND COMPRESSION. DECOMPRESSION OF VIDEOS. IMAGE DECRYPTION AND DECOMPRESSION. DATA EXTRACTION. SOFTWARE REQUIREMENTS. CONCLUSION. REFERENCES.

ABSTRACT Novel reversible data hiding scheme for encryption image. After encrypting the entire data of an uncompressed image by a stream cipher. The additional encrypted data can be embedded into the image by modifying a small proportion of encrypted data. With an encrypted image containing additional data. One may firstly decrypt it using the encryption key.

ABSTRACT(CONTI…) The decrypted version is similar to the original image. According to the data-hiding key, with the aid of spatial correlation in natural image. The embedded data can be successfully extracted and the original image can be perfectly recovered.

ABOUT THE DOMAIN In image processing is any form of signal processing for which the input is an image, such as a photograph or video frame. The output of image processing may be either an image or a set of characteristics or parameters related to the image. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it.

EXISTING SYSTEM In the existing Reversible techniques one can hide the secrete data in one or two bits of an image. When the secret data is hided in three or more bits of the image it’s quality becomes low. The human eye can detect the changes in the image. Hence, it’s data carrying capacity and the tamper resistance or security is low.

EXISTING SYSTEM DIAGRAM

PROPOSED SYSTEM A content owner encrypts the original uncompressed image using an encryption key to produce an encrypted image. A data hider embeds additional data into the encrypted image using a data-hiding key though he does not know the original content. With an encrypted image containing additional data,a receiver may firstly decrypt it using the encryption key.

PROPOSED SYSTEM The decrypted image is similar to the original image. According to the data-hiding key, he can further extract the embedded data and recover the original image from the decrypted image.

PROPOSED SYSTEM DIAGRAM

CLASSIFICATION OF MODULES There are 6 modules in our project. They are 1.Image and Data Encryption. 2.Data Embedding and Compression. 3.Splitting of Videos and Compression. 4.Decompression of Videos 5.Image Decryption and decompression. 6.Data Extraction.

IMAGE AND DATA ENCRYPTION First we want to select the image in which the data has to be hidden. First we use authentication keys to know whether the sender and receiver are authorized person. We are going to encrypt the image using the blowfish algorithm. Then we have to select the data that should be hidden inside the image.

IMAGE AND DATA ENCRYPTION(CONTI…) We have to compress the data in order to hide it. Again we are going to encrypt the data using the blowfish algorithm.

BLOWFISH ALGORITHM There are two parts to this algorithm; – A part that handles the expansion of the key. – A part that handles the encryption of the data. The expansion of the key: break the original key into a set of subkeys. Specifically, a key of no more than 448 bits is separated into 4168 bytes. There is a P-array and four 32-bit S-boxes. The P-array contains bit subkeys, while each S-box contains 256 entries. The encryption of the data: 64-bit input is denoted with an x, while the P-array is denoted with a Pi (where i is the iteration).

BLOWFISH ALGORITHM KEY EXPANSION Blowfish has a 64-bit block size and a key length of anywhere from 32 bits to 448 bits ( bits in steps of 8 bits; default 128 bits). It is a 16-round Feistel cipher and uses large key- dependent S-boxes. It is similar in structure to CAST- 128, which uses fixed S-boxes.

BLOWFISH ALGORITHM KEY EXPANSION Initialize the P-array and S-boxes XOR P-array with the key bits. For example, P1 XOR (first 32 bits of key), P2 XOR (second 32 bits of key),... Use the above method to encrypt the all-zero string This new output is now P1 and P2 Encrypt the new P1 and P2 with the modified subkeys This new output is now P3 and P4 Repeat 521 times in order to calculate new subkeys for the P-array and the four S-boxes

BLOWFISH ALGORITHM(DIA…)

DATA EMBEDDING AND COMPRESSION The data hider segments the encrypted image into a number of nonoverlapping blocks sized by s*s. For each block, pseudo-randomly divide s*s the pixels into two sets s0 and s1 according to a data hiding key. Here, the probability that a pixel belongs to s0 or s1 is ½. If the additional bit to be embedded is 0.

DATA EMBEDDING AND COMPRESSION(CONTI…) Flip the three least significant bit(lsb) of each encrypted pixel in s0. According to the scheme of lsbmr, two secret bits can be embedded into each embedding unit. Therefore, for a given secret message m,the threshold t for region selection can be determined as follows.

DATA EMBEDDING AND COMPRESSION(CONTI…) Let eu(t) be the set of pixel pairs whose absolute differences are greater than or equal to the parameter t. Here we compress the image with a additional data. Because in the base paper they studied that the pixels are broken. We use lossless algorithm for compression.

WORKING OF JPEG ALGORITHM The operation of the baseline JPEG algorithm can be divided into three basic stages 1. The removal of the data redundancy by means of the DCT. 2. The quantization of the DCT coefficients, using weighting functions optimized for the human visual system. 3. The encoding of the data to minimize the entropy of the quantized DCT coefficients. The entropy encoding is done with a Huffman variable-word- length encoder.

WORKING OF JPEG ALGORITHM(CONTI…) However, the best compression results are achieved if the color components are independent (noncorrelated). Such as in YCbCr, where most of the information is concentrated in the luminance and less in the chrominance. RGB color components can be converted via a linear transformation into YCbCr components as the equation below shows.

DIAGRAM FOR WORKING OF JPEG ALGORITHM

SPLITTING OF VIDEOS AND COMPRESSION Here we should first split the videos in the form frames by freezing the moving videos. Then we should insert the images that we have encrypted within the frames of the videos. We should compress the images inside the videos so that they can fit inside the videos and should not show that the sent with the videos. Here we are using mpeg algorithm for compression.

WORKING OF MPEG ALGORITHM The I-frames are intra coded, i.e. they can be reconstructed without any reference to other frames. The P-frames are forward predicted from the last I- frame or P-frame, i.e. it is impossible to reconstruct them without the data of another frame (I or P). The B-frames are both, forward predicted and backward predicted from the last/next I-frame or P- frame, i.e. there are two other frames necessary to reconstruct them. P-frames and B-frames are referred to as inter coded frames.

WORKING OF MPEG ALGORITHM(CONTI…) But this model assumes that every change between frames can be expressed as a simple displacement of pixels. But the figure to the right shows this isn't true. The red rectangle is shifted and rotated by 5° to the right. So a simple displacement of the red rectangle will cause a prediction error. Therefore the MPEG stream contains a matrix for compensating this prediction error.

WORKING OF MPEG ALGORITHM(CONTI..) Thus, the reconstruction of inter coded frames goes ahead in two steps: Application of the motion vector to the referred frame; Adding the prediction error compensation to the result;

DIAGRAM FOR WORKING OF MPEG ALGORITHM

DECOMPRESSION OF VIDEOS Here we have to give the authorization key to know whether you are authorized person or not. Next you have to decompress the received videos using the same algorithm and separate the videos and the images.

IMAGE DECRYPTION AND DECOMPRESSION When having an encrypted image containing embedded data. A receiver firstly generates ri, j, k according to the encryption key. Calculates the exclusive-or of the received data and ri, j, k to decrypt the image. We denote the decrypted bits as bli, j, k. Clearly, the original five most significant bits(MSB) are retrieved correctly.

IMAGE DECRYPTION AND DECOMPRESSION(CONTI…) For a certain pixel, if the embedding bit in the block including the pixel is zero and the pixel belongs to s1. The embedded bit is 1 and the pixel belongs to s0. The data-hiding does not affect any encrypted bits of the pixel. So, the three decrypted LSB must be same as the original LSB. Implying that the decrypted gray value of the pixel is correct.

IMAGE DECRYPTION AND DECOMPRESSION(CONTI…) On the other hand, if the embedded bit in the pixel’s block is 0 and the pixel belongs to s0. The embedded bit is 1 and the pixel belongs to s1. The image is decrypted using the authentication keys. Before it goes into this section the image is decompressed.

DATA EXTRACTION The receiver will extract the embedded bits and recover the original content from the encrypted image. According to the data-hiding key, he may segment the decrypted image into blocks and divide the pixel in each block into two sets in a same way. For each decrypted block, the receiver flips all the three LSB of pixels in s0 to form a new block.

DATA EXTRACTION(CONTI….) Flips all the three LSB of pixels in s1 to form another new block. We denote the two new blocks as h0 and h1. There must be that either h0 or h1 is the original block. Another one is more serious interfered due to the LSB flip operation. For the two blocks sized by s*s, define a function to measure the fluctuation in them.

SOFTWARE REQUIREMENT HARDWARE REQUIREMENTS RAM : 1GB HARDDISK : 80GB PROCESSOR : INTEL PENTIUM SOFTWARE REQUIREMENTS MATLAB 10.0 RATIONAL ROSE

CONCLUSION Here we double encryption and double compression in order to provide very high quality and security. In the way we hide the data in the videos will give more security to the data. It becomes difficult for the third party to hack the data. They can easily caught if they try to it. Here the sender and the receiver will fell free at the data will be send in a more secured manner.

CONCLUSION(CONTI…) Here we give high quality for the image by compressing it. Here we use colored image for the data to hide. So it gives even more quality and even tougher for the hackers to hack the data

REFERENCES [1]X.Zhang, “separable reversible data hiding in encrypted images”, IEEE transaction.image forensic.,vol.7,no.2,apr.2012 [2] M. Johnson, P. Ishwar, V. M. Prabhakaran, D. Schonberg, and K.Ramchandran, “On compressing encrypted data,” IEEE Trans. SignalProcess., vol. 52, no. 10, pp. 2992–3006, Oct [3] X. Zhang, “Reversible data hiding in encrypted image,” IEEE Signal Process. Lett., vol. 18, no. 4, pp. 255–258, Apr

THANKS THANK YOU