FPGA IMPLEMENTATION OF HIDING INFORMATION USING CRYPTOGRAPHIC KEY

¹Sagar Dalal, ²Prof.Mrs.K.N.Kasat

Abstract:

The growth of high speed computer networks and that of Internet, in particular, has explored means of new business, scientific, entertainment, and social opportunities. Digital media offers several distinct advantages over analog media, such as high quality, easy editing, high fidelity copying etc. The ease by which a digital information can be duplicated and distributed has led to the need for effective copyright protection tools. Various software products have been recently introduced in attempt to address these growing concerns. It is done by hiding data (information) within digital audio, images and video fles. One way such data hiding is digital signature, copyright label or digital watermark that completely characterizes the person who applies it and, therefore, marks it as being his intellectual property. Digital Watermarking is intended by its developers as the solution to the need to provide value added protection on top of data encryption and scrambling for content protection. Here the digital watermarking techniques used are DWT and DeT with grayscale image and colour image and binary Image. The High security 128 bit cryptographic key is used for the information hiding and that cryptographic key is made of fingerprint and iris. Several attacks were done to ensure that the information hiding is more secure.

Keywords-FPGA , Security, Cryptography

I. INTRODUCTION

Watermarking is the process that embeds data called a Watermarking or digital signature or tag or label into a multimedia object such that watermark can be detected or extracted later to make an assertion about the object. The object may be an image or audio or video. A simple example of a digital Watermarking would be a visible “seal” placed over an image to identify the copyright. However the watermark might contain additional information including the identity of the purchaser of a particular copy of the material. Digital Watermarking is the process that embeds data called a watermark into a multimedia object such that watermark can be detected or extracted later to make an assertion about the object. Watermarking is either “visible” or “invisible”. Although visible and invisible are visual terms watermarking is not limited to images, it can also be used to protect other types of multimedia object. The watennarking scheme (algorithm) consists of three parts: The Watermarking The encoder (marking insertion algorithm) Karthigaikumar P Department of Electronics and Communication Karpagam College of Engineering Coimbatore, India The decoder and comparator (verification or extraction or detection algorithm) Each owner has a unique watermark or an owner can also put different Watermarking in different objects the marking algorithm incorporates the watermark into the object. The verification algorithm authenticates the object determining both
the owner and the integrity of the object. Watermarking techniques can be divided into various categories in numerous ways(Mohanty S.P .1999 et.al.) . The watermarking can be applied in spatial domain as well as in frequency domain. Frequency domain methods are more robust than the spatial domain techniques but spatial domain provides facility of real time implementation through hardware realization because of lesser computational complexity. The major tenant in digital watermarking is that there are three necessities of imperceptibility, capacity and robustness that need to be fulfilled. It continuously conflict with each other. It causes trade-off among fidelity and robustness. Therefore, the projected solution is to embed a watermark image within the pixels of the cover image in spatial domain technology, but still there are some problems,

• when an image is being embedded, it shouldn’t cause any visual modifcation to the cover image.
• the image is resticted by its dimensions, so the number of bits that are utilizable for embedding is also limited . To solve these problems, least signifcant bit (LSB) plane modifcation is used for data hiding (P.Fitzmann.1996).
  Sofware implementations have been developed due to the ease of use, upgrading and flexibility but at the cost of limited speed problem and vulnerability to the offline attack. On the other hand hardware realizations offer advantage over the former in terms of area, execution time and power .

II. RELATED WORK

1. Presented a semi-blind reference watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) for copyright protection and authenticity. Their watermark was a gray scale logo image. For watennark embedding, their algorithm transformed the original image into wavelet domain and a reference sub-image is fonned using directive contrast and wavelet coefficients. Then, their algorithm embedded the watermark into reference image by modifing the singular values of reference image using the singular values of the watermark.
2. proposed a self-embedding watermarking scheme for digital images. In their proposed algorithm they used the cover image as a watermark. It generates the watennark by halfoning the host image into a halfone image. Then, the watermark is permuted and embedded in the LSB of the host image. The watermark is retieved fom the LSB of the suspicious image and inverse permuted.
3. used the PKI (Public-Key Infastucture), Public-Key Cryptography and watennark techniques to design a novel
   testing and verifing method of digital images. The main idea of their paper is to embed encryption watermarks in the least signifcant bit (LSB) of cover images.[3] He, H. J., Zhang, J. S. and Tai, H. M., (2006), A Wavelet-Based Fragile
   Watermarking Scheme for Secure Image Authentication. Springer-Verlag Berlin Heidelberg 2006 This paper proposed a wavelet-based fagile watermarking scheme for secure image authentication. In their proposed scheme, they generated the embedded watermark using the discrete wavelet tansform (DWT), and then they elaborated security watermark by scrambling encryption is embedded into the least signifcant bit (LSB) of the host image.
4. proposed a fagile watermarking scheme for authentication of images. They used singular values of singular value decomposition (SVD) of images to check the integrity of images. In order to make authentication data, the singular values are changed to the binary bits using modular arithmetic. Then, they inserted the binary bits into the least signifcant bits (LSBs) of the original image. The pixels to be changed are randomly selected in the original image.
5. Paper proposed Bit Plane Index Modulation (BPIM) based fragile watennarking scheme for authenticating RGB color image. By embedding R, G, B component of watennarking image in the R, G, B component of original image, embedding distortion is minimized by adopting least significant bit (LSB) alteration scheme. Their proposed method consists of encoding and decoding methods that can provide public detection capabilities in the absences of original host image and watermark image.
6. A wide spectrum of systems require reliable personal recognition schemes to either confirm or detennine the identity of an individual person. This paper considers multimodal biometric system and their applicability to access control, authentication and security applications. Biometric identification and recognition systems may have the following components:

7. paper discusses a new method which uses an entropy based feature extraction process coupled with Reed-Solomon error correcting codes that can generate deterministic bit sequences form the output of an iterative one-way transform. The transform employed by the system is an iterative, chaotic, bi-spectral one-way transform that accepts a one dimensional vector input and is used to produce a magnitude and angle pair per iteration. The transform incorporates similarity transformation invariance and shape sensitivity by design. This output can be converted to binary to for a very large bit matrix. These matrices are analyzed to locate feature bits suitable to be used as part of the bio-key using an entropy based criteria. The tansform requires a ID input vectors and the Radon transform is used to convert a 2D image into a set of lD projection.

III. CRYPTOGRAPHIC KEY GENERATION

Information hiding using biometric key to enhance thesecurity is the main work has to be done here. First part of the
work is biometric key generation and after that information hiding using several techniques such as LSB,DCT and DWTusing images. Multiple biometric traits are successfully utilized to attain user authentication. The following are very few good advantages of multimodal biometrics

1. improved accuracy
2. in case if sufficient data is not extracted form a given biometric sample, it can serve as a secondary means of enrolment as well as verification or identification and
3. the capability to identify endeavors to spoof biometric systems via non-live data sources particularly fake fingers. Figure 3.1 explains the design methodology.

The steps involved in the proposed approach based on multimodal biometrics for cryptographic key generation are,

1. Extraction of minutiae points fomfmgerprint
2. Extraction of features form iris
3. Feature level fusion of fingerprint and iris features
4. Cryptographic key generation form fused features

DESIGN METHODOLOGY

A watennarking system consists of three parts: the watermark, the encoder, and the decoder. The encoding
algorithm integrates the watermark in the object, whereas thedecoding algorithm validates the object by determining thepresence of the watermark and its actual data bits. Biometricswhich deals with the science of recognizing a person on thebasis her/his physiological or behavioral traits has started toachieve acquiescence as a genuine method for identifying an person’s identity. Biometric technologies have confirmed itsimportance in the fields such as security, access control and monitoring applications. Conventional authentication
methods, biometric systems provides various advantages that are numbered below.

1. Using direct covert observation, a biometric information can’t be attained
2. reproduction and sharing is impracticable
3. By easing the necessity to keep in mind lengthy and random passwords, it augments user expediency
4. It safeguards against negation by the user.

The important biometric characteristics currently in use includes fingerprint, DNA, iris patter, retina, ear, face, thermo gram, gait, hand geometry, palm-vein patter, keystroke dynamics, smell, signature, and voice .The different tests were doing for to find out the most randomness key.

IV. EXPERIMENT AND RESULTS

All the methods and algorithms described in this dissertation were implemented using MATLAB 7.10.0a on the Windows 7 operating system. Where appropriate, the experiments for some stages were conducted on a set of synthetic test images. The majority of the realfmgerrint images used in the experiments were obtained form the National Institute of Standards (NIST) fmgerprint data set and the iris images used in the experiments
were obtained form the CASIA iris Databases. The methods used for watermarking are LSB,DCT and DWT and several attacks also done to verify the retrieval of hidden information. Fig. 3 shows a prototype and a hardware block diagram of iPMD. The main processor is a 16-bit micro controller unit (MCU). It is used for performing the main tasks such as complex event processing, processing of priority based scheduling algorithm, the provision of a cloud service, situation analysis, and patter generation. A ZigBee transceiver is used for communication with other iPMDs, iEMDs or networked devices. We used a 250 kbps/2.4 GHz ZigBee tansceiver module. The metering circuit plays a role in measurement of the power consumption and observation of the power state. The power group is composed of a Switched-mode power supply (SMPS) and a power regulator. The LCD display unit shows a
variety of information such as power, voltage, and curent as well as temperature and humidity. The relay is used for
shutting off the standby power, and also used for remote contol.

Histogram Equalization

Histogram equalization increases the contrast of images, especially when usable data of the image represented by close contast values. Perceptional information of the image is increased through Histogram equalization. It permits pixel value to expand. Histogram equalization converts range from 0 to 255 which will enhance visualization effect.

Gaussian Low Pass Filter: The Gaussian low-pass filter is used as to blur an image shown in fg 5.4. The Gaussian filter generates a ‘weighted average’ of each pixel’s neighborhood, with, the average weighted more towards the value of the i central pixels.

V. CONCLUSIONS AND FUTURE WORKS

The results investigates the classification, attacks and methods of image watermarking and evaluates LSB based
digital watermarking scheme with different bit substitution form LSB to MSB in image and DCT and DWT.
Watermarking is a pattern of bits inserted into a digital image, audio or video flee that specifies the flu’s copyright
information such author, rights and so on . Thus, watermarking approach is used to make sure of the protection of the data. The actual bits representing the watermark must be scattered throughout the fle in such a way that they cannot be identified and tampered. Thus, the watermarking must be robust enough so that it can withstand
normal changes to the flee such as attacking by adding noise .Biometric key is used as secret code .That it ensures double layer security. LSB, DCT and DWT technique were used to overcome the attacks and it extract the embedded data.

Multiple image hiding and text hiding are also implemented here but the multiple usage causes the reduction of PSNR and quality of image. Biometric key is used as secret code, and it ensures double layer security.

REFERENCES

1. Aliwa Mehemed Bashir, El-Tobely Tarek EI-Ahmady, Fahmy Mahmood M., Nasr Mohamed EL Said and EI-Aziz Mohamed Hashem Abd;(2010) “A New Novel Fidelity Digital Watermarking Based on Adaptively Pixel- Most-SignifcantBit-6 in Spatial Domain Gray Scale Images and Robust”,American Joural of Applied Sciences 7 (7): 987-1022.
2. Arun Ross and Anil K Jain,(2004) “Multimodal Biometrics: An Overview”, in proceedings of the 12^th European Signal Processing Conference, pp. 1221-1224.
3. Andrew Rukhin, Juan Soto, James Nechvatal,Miles Smid, Elaine Barker, Stefan Leigh, Mark Levenson, Mark Vangel, David Banks, Alan Heckert, James Dray, San Vo(May 2001): “A Statisticel Test  uite For Random And Pseudorandom Number Generators For Cryptographic Applications”NIST Special Publication 800-22,pp 132-136.
4. A.M. Bazen and S.H. Gerez(2002) “Systematic methods for the computation of the directional felds and singular points of fngerprints”, IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 24, no.7, pp.905-919.
5. A. Jagadeesan, KDuraiswamy (2010) “Secured Cryptographic Key Generation fom Multimodal Biometrics:
   Feature Level Fusion of Fingerprint and Iris”, International Joual of Computer Science and Information Security, IJCSIS, vol. 7, no. 2, pp. 28-37.
6. Basu A., Das T.S., Sarkar S.K., Roy A., Islam N.; (Dec 2002): FPGA prototype of visual information hiding, IEEE
   Annual India Conference (INDICON), kolkata, pp 17-19 .
7. Chang c.c. and Chuan J. C.,(June 2002) -An image intellectual property protection scheme for gray-level images using visual secret sharing strategy,Patter Reconition Letters, vol. 23, pp. 931-941.
8. D. E. Knuth (1998), The Art of Computer Programming. Vol. 2, 3rd ed. Reading: Addison-Wesley, Inc., pp. 61-80.
9. Feng Hao, Ross Anderson and John Daugman(2006) “Combining Crypto with Biometrics Effectively”, IEEE
   Transactions on Computers, vol. 55, no. 9, pp. 1081 – 1088.
10. G. Langelaar, I. Setyawan, R.L. Lagendijk, (September 2002)”Watermarking Digital Image and Video Data”, in IEEE Signal Processing Magazine, Vol 17, pp 20-43,
11. Greenberg, S. Aladjem, M. Kogan, D and Dimitrov, I (2000)” Fingerprint image enhancement using fltering techniques” in Proceedings of the 15th Interational Conference on Patter Recognition, vol.32, pp. 322-325.
    
12. Haiping LU’, Xuxia Shy, Yun Q. Shit, Alex C. Kot’ and Lihui Chen (2002), “Watermark Embedding in DC Components of DCT for Binary Images”,IEEE Trans.Image Processing ,vol 8 pp 35-44.