ROBUST LOSSLESS WATERMARKING OF RELATIONAL DATABASES USING

MULTIMEDIA DATA

CONTENTSINTRODUCTION EXISTING SYSTEMRELATED WORKSPROBLEM STATEMENTOBJECTIVEMETHODOLOGYIMPLEMENTATION REQUIREMENTSRESULTS AND DISCUSSIONSPUBLICATIONSSCREEN SHOTS CONCLUSION SCOPE FOR FUTURE STUDYREFERENCES 2

INTRODUCTION Watermarking? The watermark describes information that can be used for proof of ownership or tamper proofing.

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Visible Watermark4

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

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

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

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

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

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

Subset Deletion Attack39

Subset Alteration Attack40

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

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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[12] Yong Zhang, Xiamu Niu, Dongning Zhao, Juncao Li, and Siming Liu,“Relational database watermark technique based on content characteristic”, In Proc of the First International Conference on Innovative Computing, Information and Control, 2006.

[13] Xiangrong Xiao, Xingming Sun, Minggang Chen,“Second-LSB-dependent robust watermarking for relational database”, Third International Symposium on Information Assurance and Security, 2007.

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[16 ] Ashraf Odeh and Ali Al-Haj,“Watermarking relational database systems”[17] Hsien-Chu Wu, Fang-Yu Hsu, and Hwang-Yu Chen, “Tamper detection of

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[19] Christophe De Vleeschouwer, Jean-François Delaigle, and Benoît Macq, "Circular Interpretation of Bijective Transformations in Lossless Watermarking for Media Asset Management", IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 5, NO. 1, MARCH 2003.

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