CHAPTER 5 AUDIO WATERMARKING SCHEME INHERENTLY ROBUST TO MP3 COMPRESSION

CHAPTER 5 AUDIO WATERMARKING SCHEME INHERENTLY ROBUST TO MP3 COMPRESSION In chapter 4, SVD based watermarking schemes are proposed which met the requirement of imperceptibility, having high payload and are robust to most common signal processing attacks. But, the problem is that when the watermarked audios are compressed at a higher compression i.e. compression at lower bit rate, the percentage retrieval of the watermark is reduced. Since the audios posted on the networked environment i.e. WWW are mostly mp3 audios compressed at different compression rate, there is a need to develop a watermarking scheme which is inherently robust to compression attack at different bit rate or which is applicable to compressed audios. Schemes presented in Section 4.3.1 and Section 4.3.2 are having a high payload and can be considered as a good candidate that qualifies for making a scheme which is inherently robust to compression attack by selection of the blocks that resists compression. It s always a better idea to do a preliminary analysis of the mp3 attack on the individual blocks before finally embedding the watermark for making a watermarking scheme robust to mp3 compression. Scheme presented in Section 4.3.2 shows more robustness than Scheme presented in Section 4.3.1therefore the former scheme is selected for embedding of watermark. So, in this chapter a dual pass audio watermarking scheme using the second norm/third norm of the group of SVs inherently robust to compression attack by block selection is proposed. In the Scheme presented in Section 4.3.2 all the blocks are selected for watermark embedding but in the proposed scheme the block selection is based on robustness of the block to mp3 attack. The chapter is organized in 4 sections. Section 5.1 gives the analysis of some of the audio watermarking schemes used for mp3 audios and the idea which lead to problem statement. Section 5.2 presents our proposed watermarking scheme which makes the watermarked audio inherently robust to compression mp3 attack followed by results of the experiments in Section 5.3. The chapter is summarized in Section 5.5. 113

5.1 Analysis of Some Audio Watermarking Schemes for Mp3 Audios and Problem Statement Most of the audios posted on WWW are posted in a compressed form. The compressed audios require a lesser space as far as memory is concerned. The mp3 compression is considered as a good compression technique in which the audibility of the audio doesn t change too much. The original and the compressed audio sound almost imperceptible. So, as far as embedding of watermark on a compressed audio or a watermarked audio robust to compression is concerned, there are two options. One option is to develop an audio watermarking scheme for compressed mp3 audios and the second option is to develop an audio watermarking scheme on which mp3 compression won t have any effect. There are some schemes developed for option 1. Qiao [120] proposed two audio watermarking schemes for MPEG encoded audios. In the first scheme the header of the audio mpeg file is used to embed watermark. In the second scheme the mpeg encoded samples are used for watermark embedding. For imperceptibility requirement only few encoded samples are used for embedding. The disadvantage of the approach is the weakness in sustaining the re-quantization and noise addition attacks. D. K. Koukopoulos [121] also proposed a blind digital watermarking scheme for mp3 audio files. The audio watermarking is done on the compressed audio directly. For watermark embedding, the scale factor is manipulated. The scheme claimed to overcome the disadvantage of the schemes operated on PCM coded audios which are vulnerable to compression/recompression attacks. Rade Petrovic [122] proposed a scheme in which prior to compression using AAC, multiple copies of the audio is produced and on each copy a single watermark bit is embedded. After perceptual compression using MDCT, a multiplexer is used to perform the task of selection of compression unit according to the code. Neuber et. al. [123] did it for AAC MPEG- 2 bit stream. For getting the frequency information, Huffman coding and de-multiplexers are used. The problem with the approach is the imperceptibility which is not guaranteed because of the unavailability of precise perceptual information at the embedding side. Cheng also proposed scheme for AAC audios in which watermark is embedded directly on to the quantization indices. Further, enhanced spread spectrum based scheme is used to improve the payload and robustness. The watermarked audio 114

showed robustness against compression attacks but the experimentation for checking the robustness against other signal processing attacks were not conducted and reported. There are two main problems that are associated with the schemes that embed watermark directly on the mp3 encoded coefficients and the header used for mp3 codec. One is the results of robustness against most of the signal processing operations are not favorable and the second is the transformation of the codec i.e. if the format of the audio file is changed then the header information is removed altogether which is containing the watermark information. Our scheme in Section 4.3.2 showed perfect robustness to re-sampling. Requantization, low pass filtering, extra stereo addition etc. and reasonably good robustness to other common signal processing including the mp3 compression. The robustness towards the mp3 compression using the same embedding strategy as used in Section 4.3.2 can be further be improved by selection of the blocks from which the watermark bit is perfectly retrieved i.e. without any false positive or false negative. 5.2 Proposed Scheme In this scheme, before doing the final embedding we identify the blocks that can sustain compression at different bit rates. The process of embedding requires two passes. In the first iteration the audio is watermarked with multiple watermarks using scheme of Section 4.3.2 and the watermarked audio is subjected to mp3 compression at different bit rate and again decompressed and converted into the wav file with the original bit rate. The multiple watermarks are retrieved from the audio and are compared with the original watermark. The block index corresponding to the audio is saved for which the retrieved bit is the same as the original watermark bit. The process is repeated for all the watermarked audio compressed at different bit rate. Finally a set of the block indexes is formed from the sets of perfectly retrieved watermark bit indexes which are common in all the sets. In the second pass this set of identified block indexes are used for watermark embedding. In this way all the blocks from which the watermark bit was retrieved perfectly are only used for watermark bit embedding in pass 2. Thus, an inherently robust nature against mp3 compression is 115

induced on the watermarked audio. The advantage of this approach is that the watermark is neither embedded on the compressed form nor on the header of the mp3 codec. Additionally, complex Psychoacoustic analysis is not need to be completed prior and after the watermark embedding. Next we give the elaborated algorithm for watermark embedding and watermark extraction. 5.2.1 Watermark Embedding As already mentioned two passes are required to actually embed the watermark. Pass 1 of embedding identifies the most suitable blocks for embedding. The final watermarked audio is obtained after pass 2 of embedding which uses the block identified in pass 1. The two dimensional watermark is converted into a one dimensional sequence of bits 0 and 1., ;,,, ----- (5.1) where Len = (W)=M x N 5.2.1.1 Watermark Embedding for Pass 1 For watermark embedding group of SVs are used. The second/third norm corresponding to the group of selected singular values is modified and quantized. Through the modified norm the change is scattered to the selected individual SVs. The steps involved in embedding of the multiple watermarks on to a cover audio signal are as follows: Step 1: Let X denotes the audio signal which is sampled at 44.1 khz. X { x 1,x 2,.x N } where N is no. of samples. Partition X into frames of length L. Let X i denotes i th frame. X i {x Lxi+1 x (i+1)xl-1 } 116

Step 2: Each X i is transformed into a square matrix A i of dimension u. A i = T(X i ) where T(.) is the transformation function Step 3: Perform SVD on the matrix thus formed. This operation produces the three orthonormal matrices S, U and V T as follows: [U i *S i * V i T ] = Š(A i ) where S. is the singular value decomposition function Step 4: Embedding one watermark bit Embed the binary watermark bits into the SVD-transformed audio signal using dither modulation as follows: W = {0, 1} Let Y i be the watermarked diagonal matrix then Y i = EmbedUsingNom(S i, W i,,p) // EmbedUsingNom(S i, W i,,p) is the function defined for Section 4.3.2.1 Step 5: Perform Inverse SVD Apply inverse SVD using U and V T matrices which is unchanged and S matrix which is modified in step 5 as follows: B wi = U i *S im *V i T B wi matrix is watermarked version of B i matrix obtained in step 3. Step 6: Multiple watermark bit addition Repeat step 2- step 5 on each segment to embed multiple bits on the audio signal. For one watermark the process is repeated Len times where Len is the total number of bits within one watermark. Step 7: Multiple watermark embedding Repeat step 2- step 6 on the next Len segments to embed multiple watermarks on the audio signal. 117

5.2.1.2 MP3 Compression of Watermarked Audio The watermarked audio embedded with multiple watermarks is obtained after steps given in section 5.2.1.1 are applied on the original audio. The watermarked audio is subjected to mp3 compression at different bit rates i.e. 128 kbps, 96 kbps, 64 kbps and 32 kbps. Let the audios obtained after decompression to the original watermarked wav files with original bit rate are WA 128, WA 96, WA 64 and WA 32. 5.2.1.3 Finding Block Indexes for Pass 2 Step 1: Obtain SVD Matrix Perform steps 1 through step 4 of the embedding procedure given in section 5.2.1.1 until the S matrix is obtained for all frames of the watermarked audio signal. Step 2: Extraction of multiple watermarks. For each segment of the frame, ExtractUsingNom function is called which returns the watermark bit. // ExtractUsingNom is defined in section 4.3.2.2. Step 3: Construct the watermark sequence by appending the bits retrieved from each block. Step 4: The watermark bit sequence is compared with the original watermark bit sequence and the index corresponding to the blocks from which watermark bit is retrieved successfully is stored. Step 5: Step 1 to step 4 are repeated to extract block indexes corresponding to each watermark sequence. Step 6: Store all these block indexes in a set. Let SBI bp is such a set of block indexes. 118

bps ={ 32, 64,96,128} //bps (bit per second) Step 7: Step 1 to step 6 are repeated to extract SBI bps for each bps using WA 128, WA 96, WA 64 and WA 32. Step 8: The final block indexes are given by SBI = {SBI 32 Ώ SBI 64 Ώ SBI 96 Ώ SBI 128 } Ώ -> used for intersection. //SBI is the set of block indexes for which the watermark bit is retrieved perfectly for the compression at different bit rates. 5.2.1.4 Preprocessing of Watermark For the robustness and security of the watermark, the watermark is scrambled or encrypted using Baker s chaotic map. Let the size of the image I(x, y) of the image to be embedded is M x N with M & N as the number of rows and columns respectively. Before converting the image into one dimensional binary sequence the image I (x, y) produces permuted version I`(x, y) using Baker s chaotic with security key k1. Then I`(x,y) is converted into a binary watermark using as follows, ;,,, where Len = (W)=M x N This imposes robustness for the correct estimation or removal of watermark without the use of secret key. In the best case, the extraction is that of a chaotic permuted watermark which is required to be decoded to the original watermark through the key. 5.2.1.5 Watermark Embedding for Pass 2 For watermark embedding group of SVs are used. The second or the third norm corresponding to 119

the group of selected singular values is modified and quantized. Through the modified norm the change is scattered to the selected individual SVs. The steps involved in embedding of the watermark on to a cover audio signal are as follows: Step 1: Let X denotes the audio signal which is sampled at 44.1kHz. X { x 1,x 2,.x N } where N is no. of samples. Partition X into frames of length L. Let X i denotes i th frame where i belongs to {SBI}. X i {x Lxi+1 x (i+1)xl-1 } Step 2: Each X i is transformed into a square matrix A i of dimension u. A i = T(X i ) where T(.) is the transformation function Step 3: Baker s map chaotic encryption is done on each A i to produce B i using key k of p elements B i =Ê(A i,k,p) where Ê(.) is Baker s encryption function. Step 4: Perform SVD on the matrix thus formed. This operation produces the three orthonormal matrices S, U and V T as follows: [U i *S i * V i T ] = Š(B i ) where Š is the singular value decomposition function Step 5: Embed the watermark Bit Embed the binary watermark bits into the SVD-transformed audio signal using dither modulation as follows: W = {0, 1} Let Y i be the watermarked diagonal matrix then Y i = EmbedUsingNom(S i, W i,,p) where EmbedUsingNom is the embedding function which returns the diagonal matrix after embedding and is defined in step 5 of section 4.3.2.1. Step 6: Perform Inverse SVD 120

Apply inverse SVD using U and V T matrices which is unchanged and S matrix which is modified in step 5 as follows: B wi = U i *S im *V T i B wi matrix is watermarked version of B i matrix obtained in step 3. Step 7: The decryption is done using the same key used in step 2 A i,m =Ð(B wi,k,p) where D is Baker s decryption function. Step 8: Multiple watermark bit addition Repeat step 2- step 7 on each segment X i where i SBI //All the watermark bits are embedded on the audio signal. For one watermark the process is repeated Len times where Len is the total number of bits within one watermark. 5.2.2 Watermark Extraction Step 1: Obtain SVD Matrix Perform step 1 through step 4 of the embedding procedure given in section 5.2.2.1 until the S matrix is obtained for all frames of the watermarked audio signal. The key used for making the intermediate matrix before SVD operation for every segment is the same key used for embedding in watermark embedding procedure. Step 2: Extraction of watermark bit For each segment of the frame, ExtractUsingNom function is called which returns the watermark bit. // ExtractUsingNom (Si,,p) is defined in step 2 of section 4.3.2.2. Step 3: Construct the watermark sequence by appending the bits retrieved from each segment block. Step 4: Construct the 2-d image by taking M elements corresponding to each row. The 2- d image thus formed is decrypted using the same key which is used at the time of pre processing of the watermark to obtain the final watermark. 121

In the next section, the results of experiments conducted on the same set audios are presented. 5.3 Results Since the embedding function used to embed a watermark bit on a block in Section 4.3.2 is the same function used for Section 5.2.1, the results obtained for imperceptibility in terms of SNR and robustness against all attacks used for evaluating are expected to be same except mp3 compression attack. Explicit results for imperceptibility in terms of SNR of the watermarked audio and robustness to attacks other than mp3 compression are not presented here. The first set of experiments is conducted to identify the blocks which can resist mp3 compression at different bit rates. The count of such blocks is compared against the total number of blocks used in Pass 1 for different categories of music. 10 copies of the watermarks carrying a total of 1000 bits each are embedded on the succeeding portions of the original audios. So, the total number of blocks used in Pass 1 is equal to 10,000. A comparison of the total number of blocks which resist mp3 compression against 10,000 is done to give an estimate of the number of blocks that can be used for making the scheme inherently robust to compression attack. Table 5.1 present results of the count of such blocks for different audios under different categories. Table 5.1: Count of blocks in SBI for different audios. Classical Country Pop Folk S1 6823 S1 5923 S1 6409 S1 5374 S2 6795 S2 6280 S2 6512 S2 5120 S3 6804 S3 6154 S3 6487 S3 5208 S4 6812 S4 6545 S4 6490 S4 5154 The results show that the count of blocks that can resist mp3 compression is highest for classical music category and it is lowest for folk music category. Further, table 5.2 presents the percentage of the average count of such blocks for different categories of music which gives the estimate of the payload of the scheme. 122

Table 5.2: Average Percentage count of blocks in SBI for different audios. Music Category Percentage Count Classical 0.6810 Country 0.6385 Pop 0.6482 Folk 0.5184 The result shows that the average percentage count of the SBI blocks varies from 0.52 to 0.68. This average actually gives the idea of the payload of the scheme. Almost 52 Percent of the blocks are able to resist the mp3 compression at different bit rate using scheme of Section 4.3.2.. The payload of the proposed scheme depends upon the count of such identified blocks. More is the count more will be the payload of the scheme. Since the payload of CH4PS2 is 441 bps in which all the blocks are used for watermark embedding. Using our proposed scheme by embedding the watermark bit in the selected 52 Percent of the blocks, scheme CH4PS2 can be made inherently robust to mp3 compression attack with a minimum payload of 229 bps. The robustness against mp3 compression attack is highly increased by selection of the blocks and CC of the retrieved watermark is 1 in most of the cases of audio samples. The result of robustness against different attacks given in section is presented in table 5.3. Table 5.3: Robustness against different attacks Attack CC Attack CC Requantization 1 Flip Sample 1 Resampling 1 Noise addition 0.75 Echo addition 0.91 Increase volume 0.78 Low pass 0.99 Decrease Volume 0.78 high pass 0.6 mp3 compression 1 Invert 1 LSB Zero 1 Extra stereo 1 Closed loop 1 The result shows that the proposed scheme is inherently robust to compression attacks in addition to showing good robustness to all the other mentioned attacks. Also the payload of the scheme varies from 229 bps to 300 bps. 123

Here, we are not explicitly comparing the robustness results of our proposed scheme with other schemes as it is an improvement over the scheme proposed in Section 4.3.2 for which comparison results are already given in the previous chapter. The compromise to scheme in Section 4.3.2 is only in the payload which is reduced by a maximum of 42 percent. However, the observed payload is still much higher than the contemporary schemes that are evident from the following table. Table 5.4: Payload & SNR comparison for the proposed scheme Schemes SNR(dB) Payload(bps) Proposed Scheme 29.2 229 Shahriar[118 ] 23.93 95.52 Wang [114 ] 27.23 187 Fathi [117 ] 27.18 N/A From the table it can be inferred that the proposed scheme is still having a payload which is higher than proposed by Shahriar [118], Wang [114] and Fathi [117] with almost similar SNR and robust to most common signal processing operation. 5.4 Summary In this chapter, an audio watermarking scheme inherently robust to mp3 compression is proposed based on the embedding strategy used in Section 4.3.2. The inherent robust nature against the mp3 compression attack is induced through the selection of the watermark embedding blocks which are resistant to mp3 compression. The result of robustness against other attacks also shows the effectiveness of embedding strategy and block selection. Also block selection don t has any adverse effect on the SNR of the watermarked audio. Still after selecting the blocks, the payload of our scheme varies from 229 bps to 300 bps for different content categories of music. 124