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Published in: International Journal of Speech Technology 2/2018

13-04-2018

A multi-tier security system (SAIL) for protecting audio signals from malicious exploits

Authors: N. Sasikaladevi, K. Geetha, K. N. Venkata Srinivas

Published in: International Journal of Speech Technology | Issue 2/2018

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Abstract

This paper proposes a multi-tier SegmEntation ECC Desegmentation (SEED) model to suit audio cryptosystem for Securing Audio sIgnal (SAIL) based on discrete wavelet transform and elliptic curve encryption. It is aimed with the prospect of enhancing the level of security in digital audio communication for unreliable public networks. The proposed SAIL system works as a multitier SEED model by performing segmentation, DWT compression, ECC encryption and desegmentation. In the reverse process, this multitier model proceeds with segmentation, decryption, decompression, and desegmentation. The novelty of this work relies on the adoption of ECC for encryption as it is first of its kind in audio streaming. The selection of appropriate ECC curve is a real challenge, and complex multiplication method has been applied. ECC has been chosen for encryption as it has been identified as a discrete logarithm problem which is resistant to be attacked by quantum computers. The performance of the recommended SAIL cryptosystem has been tested using different audio samples characterizing human voice, animal voice and Instrumental music. Analysis of the proposed model shows the effectiveness for fast audio encryption as it works on compressed data and also computationally simple. Various statistical analysis have been done on the proposed model, and the obtained result ratifies better level protection of audio signals from different security threats and can be recommended for multi channel audio processing.

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Metadata
Title
A multi-tier security system (SAIL) for protecting audio signals from malicious exploits
Authors
N. Sasikaladevi
K. Geetha
K. N. Venkata Srinivas
Publication date
13-04-2018
Publisher
Springer US
Published in
International Journal of Speech Technology / Issue 2/2018
Print ISSN: 1381-2416
Electronic ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-018-9510-0

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