01-08-2014, 10:42 AM
FINGERPRINTING BASED ON WAVELET & PCA
FINGERPRINTING.pptx (Size: 918.32 KB / Downloads: 14)
Introduction
Increased availability of file sharing techniques made the possibility of copyright infringement more vulnerable.
Enhance copyright protection
Digital fingerprinting is a technique for identifying users who use multimedia content for unintended purposes, such as redistribution.
Fingerprinting technique based on Wavelet and Principal Component Analysis (PCA)
Applicable in legal content distribution in P2P networks
What is a Fingerprint
A collection of marks
Unique for everyone
Digital fingerprinting – assigning a unique code word to each user
Used for identifying users who use multimedia content for unintended purposes, such as redistribution
Does not add any information
Identifies unique set of inherent properties of a media
Principal Component Analysis
Calculation of the eigenvalue decomposition of the correlation or covariance matrix of a data set
Defines the covariance structure of a set of variables
Principal components displays two characteristics:
Each component accounts for a maximal amount of variance in the observed variables
Each component is uncorrelated with all of the preceding components ( Principal components orthogonal to each other)
Peer-to-Peer networks (P2P
A distributed computing software architecture
Enables individual computers (known as peers) to connect to and communicate directly with other computers
Allows “decentralized” sharing
Advantages
Faster file transfers
Conservation of bandwidth
Saves maintenance and energy costs related to data retrieval, sharing, and processing
CONCLUSION
Unlike the conventional fingerprinting techniques, fingerprinting based on wavelet and PCA is scalable
The unique fingerprint has strong robustness against most common attacks
The fingerprinting technique based on wavelet and PCA will benefit those multimedia producers who want to share their big files, such as video files, especially in P2P networks