
	Journal of Artificial Intelligence
	Year: 2014 \| Volume: 7 \| Issue: 2 \| Page No.: 82-93 DOI: 10.3923/jai.2014.82.93

Audio Fingerprint Indicator in Embedded Platform: A Way for Hardware Steganography

Siva Janakiraman, K. Thenmozhi, John Bosco Balaguru Rayappan and Rengarajan Amirtharajan

Abstract: The increased intimidation in pilfering copyrighted multimedia files demands the imprint of ownership identity called fingerprint in video/audio files. This would aid to indentify and accuse the imitators. Several hiding methods using image, audio, video or text as cover media have been found in literature with software based implementations like MATLAB. Some of these have also been reported in hardware platforms like FPGAs. As a trade-off between these implementations, embedded devices such as ARM core were used for image steganography on gray images to embed less payload in an attempt to abide the resource constrains on embedded devices. This study suggests an indicator based random LSB coding method that embeds fingerprint on a WAV audio file. The implementation was carried out on an embedded device LPC2148 with ARM7 core housed on MCB2140 evaluation board that supports audio play through on board amplifier and speaker. The original and embedded audio signal in their digitized form resides in FLASH and SRAM on-chip memories of LPC2148.

PDF Fulltext XML References Citation Report Citation

RELATED ARTICLES:

•	Light Weight Steganography on RISC Platform-Implementation and Analysis

•	Why Information Security Demands Transform Domain, Compression and Encryption?

•	Arabic Text Steganography using Kashida Extensions with Huffman Code

•	Hiding Data in Video File: An Overview

•	Inverted Pattern in Inverted Time Domain for Icon Steganography

•	Pixel Authorized by Pixel to Trace with SFC on Image to Sabotage Data Mugger: A Comparative Study on PI Stego

How to cite this article:

Siva Janakiraman, K. Thenmozhi, John Bosco Balaguru Rayappan and Rengarajan Amirtharajan, 2014. Audio Fingerprint Indicator in Embedded Platform: A Way for Hardware Steganography. Journal of Artificial Intelligence, 7: 82-93.

DOI: 10.3923/jai.2014.82.93

URL: https://scialert.net/abstract/?doi=jai.2014.82.93

COMMENT ON THIS PAPER

Navigation


		Online First
		Current Issue
		Previous Issues
		Editorial Board
		Submit a Manuscript
		Guide to Authors
		Subscribe to E-alerts

Indexed In


		ASCI-Database
		Asian Digital Library
		Google Scholar
		SCIMAGO

Science Alert