Traceable content protection based on chaos and neural networks

Authors:
Shiguo Lian;Xi Chen
Affiliations:
France Telecom R&D Beijing, 2 Science Institute South Rd., Haidian District, Beijing 100080, PR China;E-Commerce Department, Nanjing University, Nanjing 210093, PR China
Venue:
Applied Soft Computing
Year:
2011

Citing 10
Cited 1

Digital watermarking

Digital watermarking
A New Symmetric Probabilistic Encryption Scheme Based on Chaotic Attractors of Neural Networks

Applied Intelligence
Parallel stream cipher for secure high-speed communications

Signal Processing
Finite Dimensional Generalized Baker Dynamical Systems for Cryptographic Applications

EUROCAST '95 Selection of Papers from the Fifth International Workshop on Computer Aided Systems Theory
Attacks on Copyright Marking Systems

Proceedings of the Second International Workshop on Information Hiding
On neural network techniques in the secure management of communication systems through improving and quality assessing pseudorandom stream generators

Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
An Introduction to Cryptography, Second Edition (Discrete Mathematics and Its Applications)

An Introduction to Cryptography, Second Edition (Discrete Mathematics and Its Applications)
Letters: A block cipher based on chaotic neural networks

Neurocomputing
Commutative Encryption and Watermarking in Video Compression

IEEE Transactions on Circuits and Systems for Video Technology
The convergence properties of a clipped Hopfield network and its application in the design of keystream generator

IEEE Transactions on Neural Networks

A novel JFE scheme for social multimedia distribution in compressed domain using SVD and CA

IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a media content encryption/decryption algorithm is designed based on a chaos system and neural networks, which generates random sequences with chaos, and encrypts or decrypts media contents with neural networks in a parallel way. In this scheme, different decryption keys can be used to recover the media content into different copies. That is, the decryption operation gets the content containing certain random sequence that can be used as the identification. With respect to this property, the scheme is used for secure content distribution. Taking the audio content for example, it is encrypted by a key at the sender side and decrypted by different keys at the receiver side. The differences between decryption keys lead to different decrypted audio copies. If one customer distributes his copy to other unauthorized customers, the chaotic sequence contained in the copy can tell the illegal customer. The performances, including security, imperceptibility and robustness, are analyzed, and some experimental results are given to show the scheme's practicability.