Department of Computer Science and Engineering,M S Ramaiah Institute of technology
ABSTRACT- Watermarking technology hasproved to be a hot technique to gain copyright protection. It includes many unique approaches to incorporate data into multimedia. Wavelet Transform (WT) is commonly used in watermarking schemes. The most preferred transform technique is Singular Value Decomposition (SVD) for robust, imperceptibility, capacity and secure digitalwatermarking. Tree Structured wavelet transform configuares two features spatial and transform domain energy.This paper presents two vulnerable attacks image watermarking scheme based on wavelet transform and singular value decomposition. Water marking based on wt-svd is robust against image corruption and other geometrical attacks. But it falls victim to two security attacks one is when the intruder claims the water marked image of legal real owner. Second is the attack which extracts watermark from an arbitrary image.SVD fails to provide rightful trustworthy ownership protection.
Index Terms: false positive problem, image watermarking, Wavelet Transform, Singuar Value Decomposition (SVD), vulnerableattack.
I.INTRODUCTION When looked into the pros of digital data, it can be losslessly reproduced but still there exits the intrusion and malicious data vulnerablities. Thus authentication,authorization and data hiding has become one of the major concern. The good and effective
watermarking algorithm design(scheme) should meet following characteristics, they are- the authorized
ownership protection, robustness to image manipulations(compression),watermark imperceptibility
and transparency,blind detection of watermarks.A digital water mark is a kind of marker covertly embedded in a noise-tolerant signal such as audio or image data. Water marking is process of hiding digital information in a carrier signal so that the watermark may be detected and extracted later to make an assertion about the object. A watermarking system defines two modules, an embedding module that embed the watermark into the host data and a detection/extraction module that detects and retrieves the embedded watermark. Depending on whether the original data should be available or not during detection. Singular value Matrix is embedded with watermark information of the host image. The host image is firstly transformed using wavelet transform or its family before performing the SVD operation. Controlling the robustness and imperceptibility of watermark is done by Scaling factor. The Redundant Discrete Wavelet Transform (RDWT)-SVD watermarking scheme  directly embeds a grayscale watermark image of the same size with host image into the singular value matrix of the RDWT-transformed host image, then gives the left and right orthogonal matrices as side information which will then be utilized in the watermark extraction stage. The RDWT-SVD watermarking scheme is robust against several image processing attacks and geometric distortions,and also at the same time it yields the high PSNR value for the watermarked image. But the RDWT-SVD is not vigorous against two vulnerable attacks described in this paper. Section II and III demonstrates Watermarking Attacks and Attacks on wavelet transform-svd image watermarking. Section IV shows the Experimental results and Section V concludes the paper.
II.WATERMARKING ATTACKS[26-30] There are many kinds of malicious attacks, resulting in a partial or even complete destruction of the information.
1.Active attacks: Attacker tries to remove or make the water mark undetectable by computer and detectors.These attacks create issues example in copyright protection,copy control etc.
2.Passive attacks:In this no damage or destruction of information is done,here attacker tries to notice the presence of watermark.
3.Forgery attacks: The intruder here adds a valid new watermark instead of removing the real one. He tries to modify protected information as he wish and implants a new given key in place of destructed one there by making the malicious image seems real and genuine.
4.Collusion attacks:Attacker here utilizes instances of the same data,containing each different watermark,to construct a new copy without any watermark.
III. ATTACKS ON WAVELET TRANSFORM-SVD IMAGE WATERMARKING This section describes the two vunerable attacks. The vulnerable attacks are with respect to authorized ownership protection and is defined as follow:
Real owner and attacker are the two parties involved. The real owner embeds the watermark image X into host image X yielding the watermarked image Xw side information (Aw and Bw). The real owner then publishesthe watermarked image Xw and retains the side information toextract the watermark image as a key to prove the imageownership.From publicly available digital media an attacker canobtain and manipulate the watermarkedimage Xw with ease. In this attack,an attacker tries to embed the counterfeit watermark image Wf into the owner watermarked image Xw . At the end ofwatermark embedding stage, an attacker obtains thewatermarked image Xwf and keeps the counterfeit sideinformation (Awf and Bwf ). Using this side information, anattacker attempts to extract the counterfeit watermark Wf fromthe real owner watermarked image Xw. By anattacker can easily claim and prove the real owner
In this attack, an image owner obtains the watermarked image Xw by embedding watermark image W into the host image X. At the end of watermark embedding process side information (Aw and Bw) is produced. The owner can extract the watermark image using the side information (Aw and Bw) from any arbitrary image Y. There occurs high correlation and visual similarity of extracted watermark image Wɵ+ with the watermark image W. However, the watermark Wɵ+ is extracted from an arbitrary image which not actually contains the watermark information W. Using this attack, the owner can claim and extract the correct watermark from arbitrary image with high NCC value.
IV. EXPERIMENTAL RESULTS
To examine robustness of the RDWT-SVD watermarking against two vulnerable attacks many experiments were conducted which includes rightful ownership attack.
1.Attack I Figure 1 (c) Lena image is taken as host image of size 512 X 512 of 8-bit gray scale (PSNR =53.99) for watermark, 8 bit gray scale cameraman image(figure 1(a)) into is used.The image is attacked by attacker to demonstrate RDWT-SVD scheme is inefficient to protect authorized ownership. Figure 1 (e) pictures the extracted watermark when attacker extracts the watermark from attacker’s Lena watermarked image (figure 1(d)) with the help of attacker’s side information Figure1(f) produce sextracted watermark from owner’s Lena watermarked image (figure 1 (c)).
Figure 1. Extracted Watermark from Attack I.
2.Attack II The RDWT-SVD scheme Lena host image is embedded with the cameraman image to retrieve Lena watermarked image and side information. Figure 2 (d-f) shows the extracted watermark from the baboon, peppers, uniform randomly image (figure2(a-c)) using cameraman side information. Extracted watermark is visually recognized as cameraman (figure 2 (d-f)). The RDWT-SVD watermarking caused false positive problem because of its fundamental flaw.
Figure 2. Extracted Watermark from Attack II.
V.CONCLUSIONS This paper focuses on the vulnerable attacks for wavelet transform and singular value decomposition water marking scheme. The existing RDWT-SVD scheme incorporates the watermark information with more capacity with partial degradation of watermarked image quality. It satisfies the criteria of robustness and imperceptibility aspects and results in satisfactory watermarking design requirements. But there by still exists the scope for fundamental flaw in RDWTSVD scheme resulting in the serious false positive problem. In future work it may include developing efficient watermark detectors to detect watermarks embedded from the attacked images.
VI.ACKNOWLEGEMENT I am grateful to management of my institution,
M S RAMAIAH INSTITUTE OF TECHNOLOGY its ideals and inspirations for having provided me with the facilities, which has made this technical paper a success.
I would like to extend regards to my HOD, Dr. K G Srinivas, Department of Computer Science and Engineering, for all his prolific rapport in all endeavours.
At this outset, I extend my sincere gratitude to my guide Dr. Monica R Mundada,Associate Professor, Department of Computer Science and Engineering for her technical guidance for the completion of my technical paper.
VII.REFERENCES  N. M. Makbol, and B. E. Khoo. “Robust blind Image watermarking
scheme based on redundant discrete wavelet transform and singular
value decomposition,” AEU-Int. J. Electron. Commun., 67 (2) (2013),
 V . Aslantas. “A singular-value decomposition –base image
watermarking using genetic algorithm,” AEU-Int. J. Electron. Commun.,
62 (5) (2008), pp. 386-394.
 O. S. Faragallah. “Efficient video watermarking based on singular value
decomposition in the discrete wavelet transform domain,” AEU-Int. J.
Electron. Commun., 67 (3) (2013), pp. 189-196.
 C. C. Lai. “A digital watermarking scheme based on singular value
decomposition and tiny genetic algorithm,” Digital Signal Processing,
21 (4) (2011), pp. 522-527.
 C. C. Lai, and C. C. Tsai. “Digital image watermarking using discrete
wavelet transform and singular value decomposition,” IEEE Trans.
Instrumentation and Measurement, 59 (11) (2010), pp. 3060-3063.
 V. Aslantas. “An optimal robust digital image watermarking based on
SVD using differential evolution algorithm,” Optics Communications,
282 (5) (2009), pp. 769-777.
 S. Dogan, T. Tuncer, E. Avci, and A. Gulten. “A robust color image
watermarking with singular value decomposition method,” Advances in
Engineering Software, 42 (6) (2011), pp. 336-346.
 W. Al-Nuaimy et. al. “An SVD audio watermarking approach using
chaotic encrypted images,” Digital Signal Processing, 21 (2011), pp.
 M. L. Miller, I. J. Cox, J. M. G. Linnartz , “A review of watermarking
principles and practices”, proceedings Digital Signal processing for
Multimedia Systems 461-482,Marcel Dekker Inc, 1999.  C. Shoemaker, Rudko, “Hidden Bits: A Survey of Techniques for
Digital Watermarking” Independent Study EER-290 Prof Rudko,
 R.liu and T. tan, “An SVD-Based Watermarking Scheme for protecting
rightful ownership”, IEEE Trans. On multimedia Vol. 4,no. 1
 Y. H. Wang, T. N. Tan and Y. Zhu, “Face Verification Based on
Singular Value Decomposition and Radial Basis Function Neural
Network”, National Laboratory of Pattern Recognition(NLPR),