Abstract

Voice over Internet Protocol (VoIP) calls are susceptible to interfere at many points by many attackers, thus encryption considered an important part in keeping VoIP. In this paper, Encryption VoIP based on Generated Biometric Key for RC4 Algorithm is proposed to encrypt the voice data before transmitting it over the network. The system uses a stream algorithm based on RC4 encryption with the new method of biometrics based Key generation technique. This system has generated complex keys in offline phase which is formed depend on features extracted using Linear Discernment Analysis (LDA) from face images. The experimental work shows that the proposed system offers secrecy to speech data with voice cipher is unintelligible and the recovered voice has perfect quality with MSR equal to zero and PSNR equal to infinity.

Highlights

  • The development in communications technology has been made persons in more need to communicate

  • The technology of Voice over Internet Protocol (VoIP) is considered as one of the most interesting technologies, since it is allowing a person in making phone calls via the internet, reducing the costs of communication when matched with traditional Public Switched Telephone Network (PSTN)

  • 2) Use the 256 bits of key previously generated by using Linear Discriminant Analysis (LDA) from face images as in figure 4 as a secret key of RC4 algorithm which is illustrated in Figure 2, this step increases the complexity of the keystream generation by RC4

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Summary

INTRODUCTION

The development in communications technology has been made persons in more need to communicate. Voice over Internet Protocol (VoIP) connects persons to put their voice call without any geographical limitation [1]

Voice over Internet Protocol
Biometric System
Biometric Cryptosystem
Biometric of Face
RELATED WORKS
PROBLEM STATEMENT
RC4 algorithm
THE PROPOSED SYSTEM
Contrast Enhancement Step
Image Resize Step
Feature Extraction Stage
Encryption Phase
Decryption Phase
RANDOM KEY ANALYSIS
ENCRYPTION QUALITY
10. TIME ANALYSIS
11. COMPARISON OF PERFORMANCE METRICS WITH RELATED WORK
12. CONCLUSION
Full Text
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