Paper Info
Title
Using Chaotic Maps for Encrypting Image and Video Content
Abstract
Arithmetic Coding (AC) is widely used for the entropy coding of text and multimedia data. It involves recursive partitioning of the range [0,1) in accordance with the relative probabilities of occurrence of the input symbols. In this paper, we present a data (image or video) encryption scheme based on arithmetic coding, which we refer to as Chaotic Arithmetic Coding (CAC). In CAC, a large number of chaotic maps can be used to perform coding, each achieving Shannon optimal compression performance. The exact choice of map is governed by a key. CAC has the effect of scrambling the intervals without making any changes to the width of interval in which the codeword must lie, thereby allowing encryption without sacrificing any coding efficiency. We next describe Binary CAC (BCAC) with some simple Security Enhancement (SE) modes which can alleviate the security of scheme against known cryptanalysis against AC-based encryption techniques. These modes, namely Plaintext Modulation (PM), Pair-Wise Independent Keys (PWIK), and Key and cipher text Mixing (MIX) modes have insignificant computational overhead, while BCAC decoder has lower hardware requirements than BAC coder itself, making BCAC with SE as excellent choice for deployment in secure embedded multimedia systems. A bit sensitivity analysis for key and plaintext is presented along with experimental tests for compression performance.
Year
DOI
Venue
2011
10.1109/ISM.2011.35
Multimedia
Keywords
Field
DocType
binary cac,chaotic arithmetic coding,cipher text mixing,arithmetic coding,coding efficiency,encrypting image,bcac decoder,video content,ac-based encryption technique,shannon optimal compression performance,encryption scheme,entropy coding,chaotic maps,recursive partitioning,channel coding,encryption,sensitivity analysis,cryptography
Computer science,Cryptography,Theoretical computer science,Encryption,Artificial intelligence,Shannon–Fano coding,Context-adaptive binary arithmetic coding,Entropy encoding,Pattern recognition,Algorithm,Ciphertext,Plaintext,Arithmetic coding
Conference
ISBN
Citations 
PageRank 
978-1-4577-2015-4
5
0.55
References 
Authors
12
3
Name
Order
Citations
PageRank
Amit Pande126924.58
Prasant Mohapatra24344304.46
Joseph Zambreno337744.73