Title
Tone code: A novel method for covert communications based on musical components
Abstract
Data hiding schemes using complete complementary codes (CCC) have been developed for image and audio signals. It has been shown that a high payload and a low bit-error-rate can be achieved by such data hiding strategies because of the ideal auto- and cross-correlation properties of CCC. In this study, a new data hiding strategy based on CCC is proposed by utilizing characteristics of musical pieces. In the proposed method, secret information is embedded into the specific frequency coefficients constructing the chord progression of the musical piece. If the completely same frequency coefficients used in the musical piece are selected to embed the secret information, they can perfectly match the pitch of the musical piece. As a result, it is expected that such a stego audio signal can be recognized by human ears as one of the components of the musical piece played on additional electronic instruments such as synthesizers. The authors name the proposed method as "Tone Code" since it can encode the secret messages into naturally recognizable musical tones. It is shown that the stego musical piece generated by the proposed method can be naturally recognized by human ears as a digital music through the subjective assessment by the practical experiment using a loud speaker. In addition, the results of the numerical experiments imply that the proposed method can transmit a large message with almost no errors even under various attacks.
Year
Venue
Keywords
2016
2016 International Symposium on Information Theory and Its Applications (ISITA)
tone code,covert communications,musical components,stego audio signal,frequency coefficients,data hiding strategy,autocorrelation properties,cross-correlation properties,bit-error rate,complete complementary codes
Field
DocType
ISBN
Audio signal,Steganography,Information processing,Computer science,Information hiding,Musical tone,Speech recognition,Digital audio,Chord (music),Loudspeaker
Conference
978-1-5090-1917-5
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
Kan Kamada100.34
Tetsuya Kojima2345.18
Parampalli Udaya331339.13