Identification of Digital Image Using Protein Folding and Unfolding Structure

The manner in which proteins, chains of amino acid residues, acquire their three-dimensional conformation has long been a subject of inquiry and many different explanations of the underlying mechanism have been proposed is the practice of imperceptibly altering a work to embed a message about that work. This technique contains two high level elements Embedder and Detector as shown in figure 1. The embedder takes two inputs. One is the payload we want to embed (e.g. either the watermark or secret message), other is the cover work in which we want to embed the payload. The output of embedder is presented as an input to the detector.

Now a day‘s watermarking is used in various fields to provide security. Some watermarking applications are • Broadcast monitoring: Identifying when and where works are broadcast by recognizing watermarks embedded in them. • Owner Identification: Embedding the identity of the copy right owner as a water- mark. • Content Authentication: Embedding signature information in content that can be later checked to verify it has not been tampered. • Copy Control: Using watermark to tell recording equipment what content may not be recorded. • Device Control: Using watermark to make devices, such as toys react to displayed content. • Legacy Enhancement: Using the watermark to improve the functionality of existing system. Watermarks are broadly classified into three categories viz. fragile, semi fragile and robust watermark. 1. Fragile watermark: A watermark that becomes undetectable after even minor modification of the work in which it is embedded. 2. Robust watermark: A watermark designed to survive on legitimate and everyday usage of content. 3. Semi fragile watermarking: A watermark that is unaffected by legitimate distortion but destroyed by illegitimate distortion.

Proposed algorithm [9] [10] [11] is bifurcated in to two major proposals. First proposal is Pixel-wise generic fragile watermarking scheme based on ARA bits using protein folding which is only used for alteration detection whereas second proposal is based on block-wise fragile watermarking using protein unfolding which detects the altered block as well as recover altered region with good approximation without changing the domain. First Proposal: Pixel-wise fragile watermarking based on ARA bits proposed algorithm is shown in figure 4 is based on ARA bits where ARA stands for Authentication, Relational and Associative bits. • Code of the CUT and classifies each statement (i.e., determining its type). • Determines whole information about the constructor, method signature. • Now, all the method of the given source file stored in an array.

m × n. Then N represents the number of pixels, N= m × n. So the gray scale value at each pixel of the image is denoted

Step 1: For a given tampered image IT we generate a pseudo-random binary matrix having dimension m_n (same size as IT) with the same secret key which was used for embedding. Step 2: For each pixel of IT , calculate the Associative bit then extract first LSB of all pixel of image IT . Compare the Associative bit with the extracted first LSB of corresponding pixel of IT . If there is mismatch, we mark those pixels as altered one. Step 3: This step is carried out for those pixels which has qualified first Associative bit test i.e. Associative bit and first LSB is matched. Calculate the relational bit by using equation and then extract the second LSB of remaining unmarked pixels. Compare it with the Relational bit. If there is mismatch then those pixels will be marked as altered pixel. Step 4: This last step is carried out for those pixels which have passed the relational bit test i.e. if no mismatch detected. From the pseudo random binary matrix we extract the binary value from the position corresponding to row and column of remaining unmarked pixels of IT We now compare the extracted binary value from pseudo random matrix and third LSB from IT . If there is mismatch, then those pixels will be marked as altered. If there will be no mismatch it means those pixels were not altered during any attack or gray scale value of altered pixel and original pixel is same.

Since we have proposed two approaches based on pixel and block wise fragile watermarking scheme hence we will discuss experimental results and comparison separately for each technique

Now, we demonstrate the effectiveness and accuracy of the proposed approach with experimental results and discuss the performance of our algorithm. The

standard image database. First of all we do some major alteration in image which ensures the change in MSBs. Series (c) of all figure having black region shows the unaltered pixel whereas white region shows altered one. Some altered pixels are undetectable because the five MSBs of those replaced pixels coincide with the original MSBs, they are regarded as ―Unhampered

This thesis proposes an image authentication and restoration approach using block-wise fragile watermarking which is based on k-medoids clustering technique. Many of the ap- proaches for image restoration, proposed earlier, were in frequency domain but suggested scheme is utterly in spatial domain. Experimental results and Table 5 show the efficiency of proposed scheme which is not only good enough to perceive the altered block with high accuracy but also able to restore those tampered blocks with good imperceptibility. K-medoids is a representative object based clustering technique which ensures that the gray level value which is used to replace other gray value within a block, belongs to the same block. Hence we take the benefit of this property of k-medoids. Clustering for each block is done by using a common characteristic hence for each element within a single cluster has same characteristics.

Anthony T. S. Ho, Xunzhan Zhu, Jun Shen, and Pina Marziliano (2008). Fragile Water- marking Based on Encoding of the Zeros of the -Transform IEEE Transactions On Information Forensic and Security, VOL. 3, NO. 3, September 2008. Eugene T. Lin and Edward J. Delp. A review of fragile watermarking. Center for Education and Research in Information Assurance and Security, Purdue University, West Lafayette, IN 47907-2086. Hongjie He, Jiashu Zhang, Fan Chen (2007). Block-wise Fragile Watermarking Scheme Based on Jiri Fridrich and Miroslav Goljan (1999). Images with Self-Correcting Capabilities. IEEE, 0-7803-5467-2/99. Mi-Ae Kim and Won-Hyung Lee (2004). A Content-Based Fragile Watermarking Scheme for Image Authentication Springer-Verlag Berlin Heidelberg, AWCC 2004, LNCS 3309, pp. 258-265.

Department of Computer Science & Engineering, Integral University, Lucknow