A Novel Watermarking Method using Geographical Random Image for Cloud Computing based on DCT Reversible Color Hiding Algorithm

Transcription

1 A Novel Watermarking Method using Geographical Random Image for Cloud Computing based on DCT Reversible Color Hiding Algorithm Mohammad V. Malakooti Faculty and Head of Department of Computer Engineering, Islamic Azad University, UAE branch, Dubai, UAE Amir Aghasharif Student of Department of Computer Engineering, Islamic Azad University, UAE branch, Dubai, UAE ABSTRACT With the fast development of Cloud computing, most of clients transfer their information and applications on the cloud to benefit from the cheap, easily accessible, and always available storage facilities. The development of the Internet has generally expanded the availability of digital data like images, audio and videos to the public. The fundamental problem in cloud computing is the security of the stored data. Digital watermarking is a technology that can used to secure the ownership of data saved on the public devices and facilitates data authentication for copyright protection of digital media. This paper explains the details of reversible color hiding for RGB image using DCT algorithm to extract the features of the favorite image and embed it into the cover image. In this paper, we have proposed a new watermarking method based on the Geographical Random Image (GRM). The random image is obtained from the Google earth map and client favorite location of the map. Since the selection of the image from Google map is random and client can easily change his favorite image location, it is impossible for the hacker to obtain the image location and corresponding generated code even using multicore systems and supercomputers. Once the RGB image is selected, then its corresponding compressed gray scale image will be obtained based on Malakooti-Khederzadeh reversible color hiding algorithm [13-15]. Our Proposed algorithm is used to hide the DCT coefficient of the random image, after the reversible color hiding algorithm is applied, into the cover image. To increase the availability and security of the stored data, we have used the Malakooti-Mansourzadeh Data Redundancy Algorithm (MMDRA) [14], a modified version of DEPSKY, to store the watermarked images into several different clouds. This algorithm secures the availability and accessibility of the stored data. Keywords: Cloud Computing, DEPSKY, DCT, Google Map, Random Image I. INTRODUCTION The Cloud Computing has received high attention among scientist, engineers, and even industrial communities due to its cheap and easy access storage facilities, as well as the reliable, secure and competitive hardware and software platforms, necessary technology for the data storage and retrieval, data processing and recovery. N. Jain and G. Kaur [1], have introduced a method for Implementing DES Algorithm in Cloud environment for Data Security. Cloud Computing relies on sharing of sources to empowers useful online facilities and provides on-demand network access to a large pool of commuting resources including the shared hardware and software facilities and services. With the use of Cloud Computing, the resource can be accessed easily around the world with the minimum controlling attempts and less communication problem and delays. The core objective of the Cloud Computing is to provide quick, secure, and reliable data storage and retrieval facilities, as well as a computational idea for the distributed model [2-3]. Cloud resource not only shared by the multiple-user but dynamically re-allocate per demand. In general the cloud computing is involved in delivering the hosted services over the internet. These services are usually divided into three main categories such as infrastructureas-a-service (IaaS), Platform-as-a service (PaaS), and Software-as-a Service(SaaS). The Cloud Computing has a good potential to decrease the cost of data storage and retrievals as well as to provide the availability, scalability, and dependability [3-4-7]. Digital watermarking is the act of hiding a message or a digital signal within the original signal where the message is related to the original signal. A good example of watermarking is hiding the patient vital information within the images taken from MRI examination of patient s head. Physicians normally use these MRI images to diagnose the ISBN: SDIWC 53

2 syndrome and to detect the patient s abnormality. For patient psychological health protection, some of these syndromes such as brain tumor, stroke, vascular problem such as arterial occlusion (blockage), cause of epilepsy (seizure), and so on need to be kept secret from patient. The watermarking process can be used to embed all syndromes and vital information related to the patients inside the MRI images after diagnosis is completed by team of professional physicians. In this type of watermarking the embedded message is the patient vital information that can be to identify the individual patients from the watermarked signal. Similarly, in video broadcasting information related to each individual can be embedded inside the video itself before transmission that can be used to detect the individual information from the watermarked video for the benefits of broadcast monitoring and individual video authentication. In most watermarking techniques the embedded signal or secret message used for watermarking purpose are not related to the original signal. The message usually can be used as the company logo, use of the favorite image or even some specific text that can be used for the ownership verification and authentication. This type of watermarking in which the secret message and original signal is not related is called Steganography but in literature most of researchers used the word of Watermarking even in the case where the message is not related to original signal. Digital watermarking has been used to apply the security, data authentication and copyright protection to the digital signals. Digital watermarking has several applications in ownership verification, copyright protection, and individual authentication. The watermarking techniques include two different algorithms, one for data embedding and one for data extraction. We have introduced the Cloud Computing security issues in section II. The image Watermarking and its feature are presented in section III. The remainder of the paper is organized to explain our proposed method, the new model of cloud computing for the data redundancy and availability as well as digital watermarking technique to secure the wireless transmitted data. II. CLOUD COMPUTING SECURITY Cloud computing is the main tool for small, medium and large companies in these days, but since many customers look for cloud computing services, the fundamental problem is security of their data. Data security is a necessary issue in cloud computing and in order to provide this security an appropriate method is required. With the introducing of multiple users and multiple enterprises, new security concerns arise. Therefore multitenancy, protection against velocity of attack, information assurance, data privacy and ownership are required. Some of the data security issues in the cloud are as following: 1. Privacy and confidentiality: privacy is one of the cloud computing concerns. So how do you make sure that the privacy of data is ensured in the cloud computing environment? Because multiple users and multiple enterprises may use same infrastructure. While users store their data on the cloud storage, the data must be accessible just by authorized people. Moreover, unsuitable access to user important data by cloud provider is another concern. Therefore, cloud users have to be assured which data on the cloud will be secret. 2. Data integrity: after preparing data security, cloud service provider has to perform mechanisms to guarantee data security and can discover what has happened to a specific data and the place of that data. Thus, as a result of that the user has to know about the original data and integrity mechanisms. For conformance, it is necessary to have accurate records for knowing what data was located in a public cloud. When it happens, which virtual machine and storage it exists within on, and where it was adapted. Based on applied data integrity, information must be protected and prevent revealing of data beyond the agreed domain. 3. Data location and relocation: cloud computing suggests an upward degree of data mobility. Always, users have no idea about the location of data, although a corporation that stores the important data in the cloud wants to know the place of the data. They also prefer to indicate the location. So it should be an agreement between cloud provider and user. Another problem is the transferring of data from one location to another. III. WATERMARKING AND FEATURES Digital watermarking consists of different ideas and methods like cryptography, stochastic theory, signal processing, network technology, probability theory and algorithm design. Digital watermarking masks the copyright data into the digital data by using of different algorithms. The secret and important data such as logo, text, serial number and images, is embedded to the digital data (images, audio, and video) to provide the security and identification of data owner [5-6]. Different characteristics of digital watermarking are as follows: 1. Imperceptibility: In watermarking method, it is impossible to see the information with human eyes and only authorized agents can recognize the important data by using certain processing. 2. Robustness: Robustness indicates that watermark information, which is embedded in data, has the capability of retrieving after different processes and attacks. So, the watermark should be robust for signal processing, geometrical transformation and attacks [7-8]. 3. Verifiability: Watermark must be able to prepare complete and safe documentation for the ownership of copyright-protected data products to show whether the information is to be secured and to control the distribution of the information, ISBN: SDIWC 54

3 determine the reliability, and monitor unauthorized copying. 4. Security: If the attacker cannot retrieve the data watermark, our method is secure, so only authorized users can access to the data. This requirement is usually achieved by the use of cryptographic keys [9-10]. 5. Capacity: Capacity of the watermarking system is the maximum amount of data, which can be placed in the cover information. Thus the number of watermark bits in data and the maximum repetition of data within an image is the watermark capacity [11-12]. IV. PROPOSED MODEL In this paper we only focused on the security of the stored images on the cloud environment but it can be applied on other kinds of information such as, voice, text, multimedia, and even movies. First of all we have to ask the user to enter the favorite location and select it on the map as its shown in the Figure 1. that image. Since the selection of favorite area is different for any user, the attacker cannot be able to retrieve the information. In the next step we have to follow the color hiding process as shown in the figure 3. Color Hiding Process: 1. Divide the main matrix into the Red, Green and Blue matrices. 2. Use the DCT Transform on each 8x8 Block of the Red, Green, and Blues matrices. 3. Scale the DCT coefficients of low frequency part in Green and Blue matrices and insert them in to the upper mid frequency and high frequency parts in Red DCT matrix. 4. Use the IDCT on the resulting DCT coefficient matrix [13-14]. Fig 1- Requested map by user In the next step the grid map is illustrated for the user to select the favorite area. Each user chooses the area based on his/her interests. Thus, it is difficult to guess the exact location of selected map by attackers. After that the image of square area should be taken and be stored for the watermarking processing, Figure 2. Fig 3- Color Hiding Process The embedding algorithm that we have used to hide the features of the main image is as following: 1. We should have a bitmap image, since imread command in Matlab program only accept bitmap images and it can divide the Bitmap Color Matrices into three blocks of 8*8 Red, Green and Blue matrices figure 3. Fig 2- Selection of favorite area Now user has to upload the image to store on the cloud, but before that the watermarking method should be applied on (1) ISBN: SDIWC 55

4 Equation 1 has divided the Red matrices into the 8*8 Blocks of image data and similar equation is applied on Green and Blue matrices. 2. Use DCT on each 8x8 block figure 3. Matrix, T, is calculate by the equation 3: (2) Fig 5- Store the watermark image into four different cloud providers (3) We consider that N=8, i and j are started from 1 to We also have applied the IDCT on each blocks of 8 x 8 to retrieve the embedded information. 4. Return back to step 1 and repeat from step 1 to 3 until all 8*8 sub-blocks have been processed. 5. When the embedding process is completed we have obtained the secure Image, which can be transferred over the network and carry the secret data with high security [ ]. In this scenario we have four copies of watermark image and can retrieve the original image just from any cloud provider. The cost of storing four copies of coded image would be high but the security is very high too [ ]. Scenario 2: When, the group image is watermarked then it will be stored into four cloud providers (AD,BC,CB,DA) or six cloud providers(ad,bc,cb,da,bc,ad) depend upon the type of the stored data, where A,B,C, and D are representative of 4-sub images. Finally we have applied the watermarking technique on main image figure 4. Fig 6- Divide the image and distribute the parts into Four cloud providers Fig 4- Watermarking Image Implementation We apply our watermark image on two different scenarios: Scenario 1: In the second scenario, Figure 6, if the cloud provider s number 2 and 3 have failed simultaneously or are inaccessible then we will lose 50% of our image information. To solve this issue we have stored image stored in parts BC and AD into two other cloud providers, totally six cloud providers to provide the high degree of security, availability, and accessibility figure 7 [ ]. In scenario 1 the group image is watermarked according to our proposed algorithm as explained before. So, the watermark image will be divided into four. This watermark image will be stored into four different cloud storages for the sake of security, data availability and accessibly figure 5. ISBN: SDIWC 56

5 REFRENCES [1]N.Jain, G.Kaur, Implementing DES Algorithm in Cloud for Data Security, VSRD-IJCSIT, Vol. 2, [2] K.S.Suresh, K.V.Prasad, Security Issues and Security Algorithms in Cloud Computing, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, Issue 10, [3]M.Kaur, M.Mahajan, Implementing various encryption algorithms to enhance the data security of cloud in cloud computing, VSRD International Journal of Computer Science & Information Technology, Vol. 2 No. 10, October Fig 7- Divide the image and distribute the parts into six cloud providers V. CONCLUSIONS AND FUTURE WORK Cloud Computing has improved the data storage and service availability but the security issues are not resolved yet. One of the most important problems in cloud computing is that the user s data are no longer under his control. Moreover, the data privacy and confidentiality issues have not been resolved. We have presented a robust Security Model for Cloud Computing Based on the Digital Watermarking. In addition to our Watermarking algorithm we have applied two different scenarios similar to DEPSKY to increment the viability and accessibility. Our algorithm has better result than Depsky model since addition Watermarking algorithm is applied before the storage process. In this paper, a lossless and high capacity data-hiding technique is proposed based on the DCT algorithm to embed the important data into the cover image. The embedding capacity calculated according to the number of DCT steps, the block size, and number of selected DCT coefficients in each block. So the embedding capacity is quite limited. To improve the embedding capacity of the cover image, we have conducted several tests for the adaptive capacity estimation based on the levels of DCT, size of image block, and number of selected coefficient in mid-frequency. The result of simulation indicates that we can change the indicated parameters and increment the embedding capacity although there is a tradeoff between the image quality and the embedding capacity. An adaptive smart algorithm is needed to calculate the maximum capacity of the embedding algorithm while the image is not distorted and its quality satisfies some predefined threshold. [4]P.Kalpana, S.Singaraju, Data Security in Cloud Computing using RSA Algorithm, International Journal of Research in Computer and Communication technology, IJRCCT, ISSN , Vol 1, Issue 4, September [5]D.Yuefa, Wu Bo, G.Yaqiang, Z.Quan, Tang Chaojing,, Data Security Model for Cloud Computing, Proceeding of IWISA 2009, Nov. 2009, P ,Qingdao, China. [6] K. Govinda, Y.Ngabirano,, Secure Data Storage in Cloud Computing Using Biometric, IJARCSSE, Vol. 2, Issue 5, May 2012,P [7] M.Marwaha, R.Bedi, Applying Encryption Algorithm for Data Security and Privacy in Cloud Computing, IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 1, No 1, P , January [8] A.Bessani, M.Correia, B.Quaresma F.Andr e Paulo Sousa, DEPSKY: Dependable and Secure Storage in a Cloud-of-Clouds, University of Lisbon, Faculty of Sciences, Portugal. [9] E.Gorelik, Cloud Computing Models, Massachusetts Institute of Technology, January [10] S. Ajoudanian, M. R. Ahmadi, A Novel Data Security Model for Cloud Computing, IACSIT International Journal of Engineering and Technology, Vol. 4, No. 3, June [11] Cloud Special Interest Group & PCI Security Standards Council, PCI DSS Cloud Computing Guidelines, February [12] A.Ross, A.K. Jain, Human Recognition Using Biometrics, Appeared in Annals of Telecommunications, Vol. 62, No. 1/2, pp , Jan/Feb [13] M.V. Malakooti, N.Mansourzdeh, A Robust Information Security Model for Cloud Computing based on the Scrambling Algorithm and Multilevel Encryption, ICCTIM, 2104, Dubai, UAE, pp [13] M.V. Malakooti, M. Khederzadeh, A Robust and Lossless Information Embedding in Image Based on DCT ISBN: SDIWC 57

6 and Scrambling Algorithms, Islamic Azad University, Proceedings of the International conference on Computing Technology and Information Management, Dubai, UAE, 2014 [14] M.V. Malakooti, N.Mansourzadeh, A Two Level- Security Model for Cloud Computing based on the Biometric Features and Multi-Level Encryption, Islamic Azad University, The Proceedings of the International Conference on Digital Information Processing, Data Mining, and Wireless Communications, Dubai, UAE, 2015 [15] M.V. Malakooti, A.Aghasharif, Prediction of Stock Market Index based on Neural Networks, Genetic Algorithms, and Data Mining Using SVD, Islamic Azad University, The Proceedings of the International Conference on Digital Information Processing, Data Mining, and Wireless Communications, Dubai, UAE, 2015 [16] M.V. Malakooti, N.Mansourzadeh, A Robust Information Security Model for Cloud Computing Based on the Scrambling Algorithm and Multi-Level Encryption, Islamic Azad University, The International Conference on Computing Technology and Information Management, Dubai, UAE, 2014 ISBN: SDIWC 58