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Introduction to watermarking
 In today’s internet environment proving ownership rights on outsourced relational databases is a crucial issue.
 For that purpose we present the mechanism for proof of
Ownership based on secure embedding of robust imperceptible watermark in relational data
 Here we formulate the watermarking relational databases as a constrained optimization problem and discuss efficient techniques to solve optimization problem to handle the constraints. our technique is resilient to watermark synchronization errors because it uses the partition approach that does not require marker tuples
 Watermarking is a technique that allow the owner of the data to embed an imperceptible watermark into the data.
 Aim and Objective
Aim:-
The main Aim of Watermarking Relational Databases is develop a mechanism for proof of ownership rights on outsourced relational databases.
Objective:-
Develop a secure, robust and imperceptible watermark
mechanism for providing ownership rights.
 Watermarking Model
 Applications of watermarking
 Copyright Protection
 Data Hiding
 Authentication and Data Integrity
 Copy Protection
 Fingerprinting
 Why Watermarking ?
 Digital Media (Video, Audio, Images, Text) are easily copied and easily distributed via the web.
 Database outsourcing is a common practice:
◦ Stock market data
◦ Consumer Behavior data (Walmart)
◦ Power Consumption data
◦ Weather data
 Effective means for proof of authorship.
◦ Signature and data are the same object.
 Effective means of tamper proofing.
◦ Integrity information is embedded in the data.
 What Makes Watermarking Databases Different?
 Dealing with multiple objects (tuples) instead of one
 Tuple order does not matter
 After dropping part of the database, the remaining part is still valuable
 Simple Example for Genetic Algorithms
NP Complete problems
Problems in which it is very difficult to find solution, but once we have it, it is easy to check the solution.

Nobody knows if some faster algorithm exists to provide exact answers to NP-problems. An example of alternate method is the genetic algorithm.
Example: Traveling salesman problem.