**5.3 Hardware results**

The architecture is designed and implemented using Verilog HDL and targeting vertex 5 xc5vlx20t-2ff323 FPGA. We synthesized on Xilinx ISE 14.7. Each input and

The inaudibility is measured using signal to noise ratio (SNR). It is a used to

where fi is original audio signal, whereas fi' is watermarked audio signal. It helps

**Robustness**: normalized correlation (NC) measure the similarity between orig-

here w is original watermark, w<sup>0</sup> defines the extracted watermark, and i and j are indices to represent the watermark image. Generally, NC is to be considered as equal to 1. The robustness performance is measured using bit error rate (BER) as in Eq. (9).

The different attacks are considered for the robustness measurement of our proposed algorithm. The detailed of each signal processing attacks are defined and

a. **Re-quantization**: original watermarked audio signal of 16 bit/sample is down re-quantized at 8 bits/sample, which further back quantized to 16 bits/sample.

**Attack NC BER NC BER NC BER** No Attack 1 0 1 0 1 0 Re-quantization 1 0 1 0 1 0 AWGN 0.999 0.003 0.995 0.005 0.999 0.002 Low-pass filter 0.999 0.001 0.997 0.004 0.999 0.001 Re-sampling 1 0 1 0 1 0 Mp3 64 kbps 0.9821 0.041 0.9878 0.037 1 0 MP3 128 kbps 1 0 1 0 1 0 Random cropping 0.997 0.002 0.999 0.001 0.998 0.002 Invert 1 0 1 0 1 0 Echo addition 0.997 0.002 0.998 0.003 0.999 0.002 Denoising 0.996 0.001 0.994 0.005 0.996 0.001 Pitch shifting 0.999 0.001 1 0 1 0

**Pop Speech Classical**

to calculate the noise induced in the watermark and defines the inaudibility.

inal and extracted is given by:

results are defined in **Table 1** [22].

**Table 1.**

**206**

*Experimental results for robustness of proposed algorithm.*

ð7Þ

ð8Þ

ð9Þ

calculate the similarity between distorted watermarked audio signal and undistorted original audio signal. SNR is calculated as in Eq. (10):

*Security and Privacy From a Legal, Ethical, and Technical Perspective*
