Spread Spectrum Audio Watermarking Using Multiple Orthogonal PN Sequences and Variable Embedding Strengths and Polarities

Xiang, Yong; Natgunanathan, Iynkaran; Peng, Dezhong; Hua, Guang; Liu, Bo

doi:10.1109/taslp.2017.2782487

Cited by 69 publications

(47 citation statements)

References 27 publications

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“…Afterwards, he starts watermark extraction by initializing G as an empty n × k matrix. Then, S i [1] Afterwards, the pairs in P * are sorted in ascending order according to the lexicographical order. For each pair, denote the modified value as Y, and the embedded bits as a.…”

Section: Watermark Extractionmentioning

confidence: 99%

“…In the last decades, researchers mainly focus on the advancement of watermarking technology in multimedia, including algorithms for audio [1][2][3], image [4][5][6][7][8], and video [9][10][11]. Researchers have also proposed many watermarking schemes for texts and databases.…”

Section: Introductionmentioning

confidence: 99%

“…are excluded according to(1) given a threshold T. Here, if the length of c k;v i is less than b, c k;v i is excluded from C k . We further sort the collection C k according to the length of the values of the cells.…”

mentioning

confidence: 99%

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Semi-structured data protection scheme based on robust watermarking

Ying

Qian

et al. 2020

J Image Video Proc.

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Semi-structured data is a widely used text format for data interchange and storage. This paper proposes a robust watermarking scheme of data protection for semi-structured data, which uses JSON format as an example for illustration. We first parse JSON file into a data structure of distinct pairs. Afterwards, we generate a transfer matrix to get the intermediate sequences, which are then encoded using error-correction codes and embedded into the pairs. A private key is shared by the data hider and the recipient to resist collusion attacks. On the recipient's side, data extraction can be successfully carried out even the received stego data are tampered. The imperceptibility is realized by embedding data into the less significant digits of numeric data in the cover file. The proposed scheme can be extended on several other formats. The experimental results show that the proposed scheme is robust to various kinds of typical attacks such as contextual truncating, modification, and redundancy addition.

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Section: Watermark Extractionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Semi-structured data protection scheme based on robust watermarking

Ying

Qian

et al. 2020

J Image Video Proc.

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“…Kode PN merupakan kode yang bersifat ortogonal dan dalam buku (Shulze & Luders, 2005) pada bab CDMA atau pada (Yani, Rizal, & Prasetya, 2008), kode PN dihasilkan dari teknik atau proses Linear Feedback Shift Register (LFSR). Proses LFSR akan menghasilkan kode random bit 0 dan 1 secara acak namun ortogonal satu sama lain, setelah itu pada (Xiang, Natgunanathan, Peng, Hua, & Liu, 2018) kode acak 0 dan 1 tersebut dilakukan proses penguraian dengan prosedur Gram Schmidt menghasilkan kode yang terdiri dari bilangan desimal dan terdistribusi Gaussian dengan persamaan probability density function (pdf) terdistribusi Gaussian sesuai yang ditunjukkan pada Persamaan (1). Umumnya…”

Section: Pendahuluanunclassified

Penyisipan Citra pada Audio dengan Kode PN Terdistribusi Gaussian

2019

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ABSTRAKPada makalah ini, perancangan audio watermarking memanfaatkan kode PN yang terdistribusi Gaussian atau Normal dengan menggunakan citra sebagai watermark yang disisipkan pada audio. Watermark yang berupa citra biner diubah ke dalam vektor 1 dimensi, kemudian dijumlahkan dengan kode PN terdistribusi normal yang disaring dengan filter psikoakustik. Setelah itu, sinyal dikalikan dengan faktor gain α sebelum dijumlahkan dengan host audio untuk mendapatkan watermarked audio. Hasil dari simulasi menunjukkan bahwa sistem memiliki kapasitas watermark yang tinggi pada 689.06 bps, imperseptibilitas yang baik pada SNR>26 dB, dan tahan terhadap serangan LPF mulai frekuensi cut off 6 kHz keatas, serangan Additive Noise mulai 40 dB keatas, resampling pada rate 16 kHz, LSC 1% - 10%, dan kompresi MP3 untuk rate 192 kbps.Kata kunci: Audio Watermarking, Kode PN, distribusi normal, filter sikoakustik ABSTRACTIn this paper, the design of audio watermarking utilizes PN code that is Gaussian or Normal distributed by using the image as a watermark inserted in the audio. The watermark in the form of binary images is converted into a 1-dimensional vector, then summed up with a normally distributed PN code filtered by a psychoacoustic filter. After that, the signal is multiplied by α gain factor before adding it to the audio host to get the watermarked audio. The result of the simulation shows that the system has a high watermark capacity at 689.06 bps, good imperceptibility at SNR> 26 dB, and withstand LPF attacks starting from 6 kHz cut-off frequency and above, Additive Noise attacks from 40 dB up, resampling at 16 kHz , LSC 1% - 10%, and MP3 compression for 192 kbps rate.Keywords: Audio Watermarking, PN code, normal distribution, psychoacoustic filter

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“…Zhang et al exploited the correlation between the host signal and the watermark as well as the bit message to be embedded to improve the decoding performance [19]. Xiang et al proposed a novel SS-based on the audio watermarking method which can not only remove the host signal interference but also maintain higher embedding capacity and better robustness [20]. Whereas, these methods all have the weakness of desynchronization attacks.…”

Section: Introductionmentioning

confidence: 99%

RFPS: A Robust Feature Points Detection of Audio Watermarking for Against Desynchronization Attacks in Cyber Security

et al. 2020

IEEE Access

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Digital watermarking is an effective covert communication technique in the military field, which can solve the problems in traditional encryption. In general, the Spread Spectrum (SS) algorithm can well satisfy the requirements of concealment and anti-interference in the covert communication process. However, it has a natural defect in resisting desynchronization attacks. In this paper, we propose a Robust Feature Points Scheme (RFPS) against desynchronization attacks by calculating the maximum response value of the second-order derivative of the original audio signal. The maximum response value will be used as a feature point and the audio segments centering at the detected feature points are extracted for both watermark embedding and extraction process. This study mainly focuses on cropping attacks and pitch invariant TimeScale Modification (TSM) attacks. The experimental results show that under non-uniform cropping attacks, the proposed method can extract the watermark information without any bit error rate. Even in the case of the pitch-invariant TSM attacks, the proposed scheme has great improvement compared with the existing works.

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Spread Spectrum Audio Watermarking Using Multiple Orthogonal PN Sequences and Variable Embedding Strengths and Polarities

Cited by 69 publications

References 27 publications

Semi-structured data protection scheme based on robust watermarking

Semi-structured data protection scheme based on robust watermarking

Penyisipan Citra pada Audio dengan Kode PN Terdistribusi Gaussian

RFPS: A Robust Feature Points Detection of Audio Watermarking for Against Desynchronization Attacks in Cyber Security

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