Download - ROBUST LOSSLESS WATERMARKING OF RELATIONAL DATABASES USING MULTIMEDIA DATA_Anju Paul-Final
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ROBUST LOSSLESS WATERMARKING OF RELATIONAL DATABASES USING
MULTIMEDIA DATA
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CONTENTSINTRODUCTION EXISTING SYSTEMRELATED WORKSPROBLEM STATEMENTOBJECTIVEMETHODOLOGYIMPLEMENTATION REQUIREMENTSRESULTS AND DISCUSSIONSPUBLICATIONSSCREEN SHOTS CONCLUSION SCOPE FOR FUTURE STUDYREFERENCES 2
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INTRODUCTION Watermarking? The watermark describes information that can be used for proof of ownership or tamper proofing.
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Visible Watermark4
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WHY WATERMARKING?
Real-world datasets can tolerate a small
amount of error without degrading their
usability
Effective means for proof of authorship
Effective means of tamper proofing
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WATERMARK DESIRABLE PROPERTIES
Detectability
Robustness
Imperceptibility
Blind System
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APPLICATIONS Broadcast Monitoring Owner Identification Proof of Ownership Authentication Transactional Watermarks Copy Control Covert Communication
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TOPIC REFERS TO: Robust? Lossless? Watermarking for Databases is one of the fastest growing areas of research Data Integrity needs to be authenticated Proposed by Vleeschouwer et al
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BACKGROUND Lot of works related to watermarking technology Images, Video, Audio Database Watermarking
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JUSTIFICATION Information security and Integrity are becoming critical areas of research Realize the importance of watermarking Security of relational database Ownership verification of data
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EXISTING SYSTEM Two fundamental stages: Message embedding Message detection/extraction Tuple grouping Operation nu= H (Ks|H (Ks|tu.PK)) mod Ng
Modulation: Modifying Attributes
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COMMON DATABASE WATERMARKING
Original Database Pretreatment Modulation Watermarked
Database
Attack
Observed DatabasePretreatmentDemodulation
Extraction/ Detection
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ATTACKS
Tuple deletion
Tuple insertion
Tuple alteration
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WATERMARKING METHODS
TECHNOLOGY USED
CONCEPT ADVANTAGES
DISADVANTAGES
Watermarking of relational database based on specific bit values [1]
Based on MAC function
The watermark insertion is a kind of bit setting. if this first hash value is even then the jth least significant bit is set to zero otherwise it is set to one
Prevent randomization attack, rounding attack, etc
Does not prevent trivial attack
Watermarking of relational database using optimization-based technique [6]
Based on constraint optimization problem
Handle tuples with multiple attributes. The Genetic Algorithm (GA) and Pattern Search (PS) methods are used to solve the problem
Resilient to data manipulation attacks
Bit-flipping attack
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RELATED WORKS
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Robust Watermarking algorithm [13]
Based on second LSB Least Significant Bits)
Groups the data by the hash value of primary key & positions with second LSB of data in every group
Robustness, blind detection, tuple orderindependent, and invisibility
Watermark will be lose with tail attack
Public key cryptography based algorithm [14]
Based on public key cryptography
The asymmetric keys are used for inserting and detecting watermark into the relational database.
Verify integrity of database
Impossible forattractor to know information about private watermark with which destroy it.
Watermarking scheme by using adaptive mechanism [15]
Based on adaptive mechanism for protecting Intellectual Property Rights (IPR)
Adopts an adaptive mechanism to select an optimal scheme to embed the watermarking for each datasheet according to its characteristics.
IPR protection of relational data
Error-correcting coding technology is required
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Most of the works concentrated on numerical attributes Most of the systems can withstand data manipulation attacks Distortion is occured
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PROBLEM STATEMENT Existing works related to embedding numerical values that are inferred from database itself Watermark is dependent on the database Bit flipping attack Capacity of watermarking is less
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OBJECTIVES Used for protecting medical database Maintaining copyright protection Eliminate drawbacks of previous works Withstand data manipulation attack Invisible to attacker’s eyes
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METHODOLOGY
High Level Design Low Level Design
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NEW WATERMARKING SYSTEM
Fragile and Robust Database Watermarking Schemes- Vleeschouwer Based on Circular Histogram Modulation Evaluation of Performance
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HOW IT WORKS?
Original Database
Group Creation
Robust Embedding
Fragile Embedding
Watermarked
Database
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Instead of Grayscale image use Colour Image Try to implement it on multimedia data, i.e. video Video is converted into frames The main aim is to improve privacy and capacity
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SYSTEM OVERVIEWOriginal Database
(Relational Database)
Pre - Treatment
Modulation
Cover Image + Database
Demodulation
Extraction
Hash Function
Circular HistogramModulation (embedding)
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LOW LEVEL DESIGN Modified Modules for colour Image
1.Creation of Hash Function 2. Creation of Image Planes 3. Modulation and Embedding 4. Demodulation and Data Recovery
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CREATION OF HASH FUNCTION
Tuple grouping operation Make the watermark independent of database index number nu= H (Ks|H (Ks|tu.PK)) mod Ng
Ks Watermarking secret key
PK primary key, Ng Non intersecting groups of tuples 25
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CREATION OF IMAGE PLANES
Colour image consists of RGB pixels
Separation of an image into two planes
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MODULATION AND EMBEDDING
Divide each planes into Nb blocks
Divide it into two sub blocks Create histograms and mapped into the circle Relative angle between both circular histogram’s center of mass is modulated
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DEMODULATION AND DATA RECOVERY
Reverse of embedding Histogram shifting
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BLOCK DIAGRAMRead Input Image
Create Image (RGB) Array
Histogram Creation
Circular Histogram Modulation
XOR Operation
Embedding Database into Image
Watermarked Image and Database
Demodulation & Extraction of data
Check Image Parameters Distortion Occurs
Relational Database
ASCII Conversion
Watermarking Key
Satisfied
Not Satisfied
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MODIFIED MODULES FOR VIDEO
Creation of Hash function Creation of Frames from Input Video
Using Indeo Video5 Software Creation of Image array from Frames Modulation and Embedding Frames to Video Conversion
Using Cinepak software Demodulation and Data Recovery
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BLOCK DIAGRAMRead Input Video
Create Image (RGB) Array
Histogram Creation
Circular Histogram Modulation
XOR Operation
Embedding Database into Frames
Watermarked Image and Database
Demodulation & Extraction of data and video regeneration
Check Image Parameters Distortion Occurs
Relational Database
ASCII Conversion
Watermarking Key
Satisfied
Not Satisfied
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ADVANTAGES Robustness against: Insertion Attack Deletion Attack Synchronization errors A large attribute set can be watermarked Watermark both numerical and categorical attributes Watermark is independent Distortion controlled watermarking 33
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IMPLEMENTATION REQUIREMENTS
Hardware Requirements Hard Disk : 6GB RAM : 1GB
Software Requirements Operating System : Windows 7 Platform : MATLAB 8.1 Image : 256*256 Video : AVI Format 34
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RESULTS AND DISCUSSIONS Verify the theoretical performance of capacity and robustness Consider a medical database with fixed number of groups Ng = 3000 Capacity depends on properties of attributes
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Capacity Depending on Shift amplitude rate 36
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With our watermarking technique, we have achieved 100 percentage watermark detection even when the database size was increased by 100 percentage. The Watermark detection rate remains constant with increase in the size of database.
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Subset Insertion Attack 38
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Subset Deletion Attack39
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Subset Alteration Attack40
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Performance in terms of its utility Consider simple relational database (six attributes) Watermarking using colour image MSE= 0.2459 Peak Signal to Noise Ratio (PSNR) value = 54.2234. The same would be done with video. The MSE value= 0.2413 PSNR value = 54.3051
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PUBLICATIONS[1] Anju Paul and Sunitha E V, "Distortion less Watermarking of
Relational Databases Based on Circular Histogram Modulation", IEEE International Conference on Circuit, Power and Computing Technologies 2015.
[2] Anju Paul and Sunitha E V, “Distortionless Watermarking of Relational Databases Based on Circular Histogram Modulation”, in Proc. IEEE Digital Library
[3] Anju Paul and Sunitha E V, “Watermarking of Relational Databases using Video”, in Proc. IJSETR-VOL-4-ISSUE-4-790-794. 2015.
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SCREEN SHOTS
43Input Colour Image
Watermarking of Relational Database using Colour Image
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Creation of Image Planes
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Histograms of Image Planes
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Circular Histogram
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Encrypted Image
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Encrypted Image Contains Data
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Original Image Contains Data
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Original Database after Decryption
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Watermarking of Relational Databases using Video
Input Video (AVI Format)
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Selection of one Frame and Separation of Image Planes
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Creation of Histograms
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Encrypted Image contains Data
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Original Image contains Data
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Original Database after Decryption
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CONCLUSION Data is a critical resource Posteriori protection Watermark both numerical and categorical attributes Performed using colour image and video Watermark potential large attributes
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SCOPE FOR FUTURE STUDY Can be implemented in 3D images Watermarking of multiple databases in multiple frames at a time
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REFERENCES[1] R. Agrawal and J. Kiernan,“Watermarking relational databases”, in Proc.
28th Int. Conf. VLDB, Jul. 2002, pp. 155-166.[2] R. Sion, M. Atallah, and S. Prabhakar,“Rights protection for relational
data”, IEEE Trans. Knowl. Data Eng., vol. 16, no. 12, pp. 1509-1525.[3] D. Gross-AMBLARD, “Query-preserving watermarking of relational
databases and XML documents”, ACM Trans. Database Syst., vol. 36, pp. 1-24, Mar. 2011.
[4] Y. Li, H. Guo, and S. Jajodia, “Tamper detection and localization for categorical data using fragile watermarks”, in Proc. 4th ACM Workshop DRM, Oct. 2004, pp. 73-82.
[5] J. Guo,“Fragile watermarking scheme for tamper detection of relational database”, in Proc, CAMAN, May 2011, pp. 1-4.
[6] M. Shehab, E. Bertino, and A. Ghafoor,“Watermarking relational databases using optimization based techniques”, IEEE Trans. Knowl. Data Eng, vol. 20, no. 1, pp. 116-129, Jan 2008.
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[7] S. Bhattacharya and A Cortesi, “A distortion free watermark framework for relational databases”, in Proc. 4th Int. Conf. Softw. Data Technol., vol. 2, Dec. 2009, pp. 229-234.
[8] I. Kamel and K. Kamel,“Toward protecting the integrity of relational databases”,in Proc. IEEE World Cong. Internet Sec., Feb. 2011, pp. 258-261.
[9] Y. Zhang, X. Niu, and B. Yang,“Reversible watermarking for relational database authentication”, J. Comput, vol. 17, no. 2, pp. 59-66, Jul. 2006.
[10] Y. Li, V. Swarup, and S. Jajodia,“Fingerprinting relational databases: Schemes and specialties”, IEEE Trans. Dependable Secure Comput., vol. 2, no. 1, pp. 34-45, Jan/Mar. 2005.
[11] ZHI-HAO ZHANG, XIAO-MING JIN, JIAN-MIN WAN, DE-YILP, “Watermarking relational database using image”, In Proc of the Third International Conference on Machine Learning and Cybernetics, Shanghai, 26-29 August 2004.
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