Ieee signal processing letters review time năm 2024

Based on the attached set of reviews, I regret to inform you that I have to decide to REJECT the paper for publication.

In summary, on the basis of the received reviews and of my personal opinion, the presented paper basically lacks of novelty and does not contain sufficient elements of comparison with other state-of-the-art techniques as evidenced by all the reviewers (see attached). Furthermore, the issue of robustness against some common audio processing attacks is not properly treated and the whole presentation of the manuscript is to be improved.

Considering that the decision process for the IEEE Signal Processing Letters is BINARY (papers that need major revisions are not accepted), I regret that I cannot offer you a more positive decision at this point because we do appreciate your interest in publishing in the IEEE Signal Processing Letters.

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Reviewer Comments:

Reviewer: 1

Recommendation: R - Reject (Paper Is Not Of Sufficient Quality Or Novelty To Be Published In This Transactions)

Comments: The manuscript presents a transparent digital data-hiding scheme for audio. The secret data is embedded into the phase information of FFT coefficients, using Rounding Reduced-Arc M-ary Phase Shift Keying (MPSK) modulation.

The main achievement of the proposed method is high capacity, even more than 21 kilobits per second. Apart from high capacity, the proposed solution also provides a high level of imperceptibility. However, the embedded information cannot be recovered with 100% fidelity even in the absence of attacks. This is a very serious shortcoming of the proposed solution.

I am afraid that the manuscript cannot be accepted due to the mentioned shortcoming. In addition, there are other major comments wrt the proposed solution that should be addressed by the authors in their future work:

1. The authors mention that the values of $\alpha$ and $n$ are coupled. The exact relationship between those parameters should be provided explicitly in the manuscript.

2. There are absolutely no details about the genetic algorithm and the parameters used for optimising the fitness function.

3. The fitness function is not explained. The contribution of BER in the fitness function is somewhat surprising. Larger BER values seem to prove a better fitness than smaller values. For example, 0.3 BER would provide better fitness than 0.1 BER. This does not appear to be reasonable.

4. The advantages (if any) of the proposed method wrt that of reference [5]:

Jose Juan Garcia-Hernandez, Ramon Parra-Michel, Claudia Feregrino-Uribe, Rene Cumplido, High payload data-hiding in audio signals based on a modified OFDM approach, Expert Systems with Applications, Volume 40, Issue 8, 2013, Pages 3055-3064.

are unknown. In fact, the proposed method is not compared with any other audio data hiding scheme.

5. Robustness is not discussed. It seems that the proposed scheme is fragile against attacks. If so, it would be useful for steganography, but there are many steganographic methods for audio with payloads much higher that 20 kbps. Hence, what would be the advantage of the proposed solution compared to audio steganography that provides much more capacity? The answer should be statistical undetectability, but such an analysis is not carried out in the manuscript.

Finally there are some minor comments:

- In general, figures are too small to be read (in some cases even with zoom).

- In equation (8), $S’_j$ is repeated.

Additional Questions: 1. Is the topic appropriate for publication in this transaction?: Yes

2. Is the topic important to colleagues working in the field?: Yes

Explain:

3. How would you rate the technical novelty of the paper?: Not Novel

4. How would you rate the English usage?: Needs improvement

6. Rate the references: Unsatisfactory (explain):

Reviewer: 2

Recommendation: R - Reject (Paper Is Not Of Sufficient Quality Or Novelty To Be Published In This Transactions)

Comments: The paper presents a digital data-hiding technique in audio signal based on Rounding Reduced-Arc M-Ary Phase Shift Keying (MPSK). The proposed embedding system is trivial, in that some very well known strategies to improve the robustness of audio watermarking are completely ignored as for example channel encoding and spread spectrum. Moreover, strategies to improve the inaudibility of audio watermarking exploiting psycho-acoustic models, are not considered at all. On the other hand, the proposed scheme is tested without considering classical type of attacks, e.g., compression, analogue palyback, white noise, etc., and hence it is impossible to evaluate the performance comparing them with those of alternatives. As a matter of fact, the references are not adequate, and they do not consider lot of papers that have treated the same issue or that are relevant for this topic:

1. Hafiz M. A. Malik, Rashid Ansari, and Ashfaq A. Khokhar. Robust data hiding in audio using allpass filters. IEEE Transactions on Audio, Speech, and Language Processing, 15(4), May 2007. 2. C. Neubauer and J. Herre. Digital watermarking and its influence on audio quality. In Proc. 105th AES Conv., San Francisco, CA, Sept. 1998. 3. D. Gruhl, A. Lu, and W. Bender. Echo hiding. In Proc. Inform. Hiding Workshop, Cambridge, U.K., June 1996. 4. A. Abrardo, M. Barni, and G. Ferrari ”Audio informed watermarking by means of dirty trellis codes,” In Information Theory and Applications Workshop (ITA), pages 1–8, 2013. 5. Petrovic R. Audio signal watermarking based on replica modulation. In TELSIKS, 2001 5th International Conference, 2001. 6. L. Boney, Tewfik A. H., and Hamdy K. N. Digital watermarks for audio signal. In International Conference on Multimedia Computing and Systems, pages 473–480, Hiroshima, Japan, 1996. 7. Cvejic. N., Keskinarkaus A., and Seppanen T. Audio watermarking using m-sequences and temporal masking. In IEEE Workshops on Applications of Signal Processing to Audio and Acoustics, pages 227–230, New Paltz, New York, 2001. 8. A. Abrardo, M. Barni, “A New Watermarking Scheme Based on Antipodal Binary Dirty Paper Coding,” IEEE Transaction of Information Forensic and Security (TIFS), September 2014 9. D. Kirovski and H. Malvar. Robust spread spectrum audio watermarking. In IEEE International Conference on Acoustics, Speech, and Signal Processing, Salt Lake City, UT, pp. 1345-1348, 2001. 10. H. Kim. Stochastic model based audio watermark and whitening filter for improved detection. In IEEE International Conference on Acoustics, Speech, and Signal Processing, 2000. 11. S.K. Lee and Y.S. Ho. Digital audio watermarking in the cepstrum domain. IEEE Transactions on Consumer Electronics, 46(3), 2000. 12. J. Seok, J. Hong, and J. Kim. A novel audio watermarking algorithm for copyright protection of digital audio. ETRI Journal, 24, 2002. 13. Byeong-Seob Ko, Ryouichi Nishimura, and Yiti Suzuki. Time-spread echo method for digital audio watermarking. IEEE Transactions on Multimedia, 7(2), April 2005. 14. Wang Y. Selected Advances in Audio Compression and Compressed Domain Processing. Tampere University of Technolog, Ph.D. thesis, 2001. 15. Arnold M. and Schilz K. Quality evaluation of watermarked audio tracks. SPIE Electronic Imaging, 4675:91–101, 2002. 16. A Abrardo, M Barni, A Gorrieri, G Ferrari , “An information-theoretic analysis of dirty paper coding for informed audio watermarking,” Information Theory and Applications Workshop (ITA), 2014, 1-6 17. Cvejic. N., A., and Seppanen T. Improving audio watermarking scheme using psychoacoustic watermark filtering. In IEEE Internation Conference on Signal Processing and Information Technology, pages 169–172, Cairo, Egypt, 2002. 18. Painter T. and Spanias A. Perceptual coding of digital audio. Proceedings of the IEEE, 4(88), April 2000. 19. Darko Kirovski and Henrique S. Malvar. Spread-spectrum watermarking of audio signals. IEEE Transactions on Signal Processing, 51(4), April 2003.

Moreover, the proposed embedding strategy is very confusing. As an example, it is not clear in equation (3) where the information is, in that the new symbol is equal to the previous one plus a phase shift Ps that, according to Fig. 1 is a constant term. If this is the case the Symbol j has zero entropy since it is equal to the previous one plus a constant term, and hence no information is embedded. In general embedding and extraction processes are not clearly presented, it is not clear if they consider a differential MPSK or not. Moreover it is not clear why they use a limited Arc to embed signals, no rationale for this choice is given.

Additional Questions: 1. Is the topic appropriate for publication in this transaction?: Perhaps

2. Is the topic important to colleagues working in the field?: Moderately So

Explain:

3. How would you rate the technical novelty of the paper?: Not Novel

4. How would you rate the English usage?: Needs improvement

6. Rate the references: Unsatisfactory (explain):

Reviewer: 3

Recommendation: R - Reject (Paper Is Not Of Sufficient Quality Or Novelty To Be Published In This Transactions)

Comments: Review of the paper: “High-Capacity and Transparent Digital Data-Hiding using Rounding Reduced-Arc MPSK”. This paper deals with a data hiding technique for embedding information in audio signals. The data is aggregated as PSK symbols in the phase domain at certain frequency components of the audio signal. In addition, a genetic algorithm is employed for identifying the best values for some of the parameters of the method. Although the paper is more or less understandable, I cannot support the current publication of it due to the following reasons: 1.- The introduced novelty is misleading and not sufficient: The proposed technique is clearly based on the proposal in [5], but the paper claimed that in this work is where the rounding of reduced arc M-ary shift keying is proposed, which is not fair, as it is precisely the contribution of [5]. Furthermore, at the beginning of section II it is said that: “…[5] who had attempted to apply…”, which is misleading, as in [5] the proposal was not only attempted, but succeeded. From my revision, I understand that the difference between the proposed technique and the one in [5] was the treating of the embedded signal, by means of (3), as a differential PSK modulation and the inclusion of the genetic algorithm for optimizing the values of the design parameters. From the perspective of this author, this is what the authors should have tried to explain. In addition, the title of the paper should also have to refer only to the new contributions. 2.- The comparison with previous works is not clearly stated: In any transactions, this is one of the most important features for guaranteeing novelty and validity of the proposed work; it means, it is mandatory to include the performance comparison of the proposed and related works, in any significant metric. This paper lacks of providing this information, as it is not clearly shown the advantage of the proposed method in contrast to [5] or any other method, aside from confirming the results provided in [5]. Therefore, this reviewers suggest the authors to show the advantages in terms of ODG and/or BER by using the proposed embedding modification and genetic algorithm, when comparing with [5] and some other previous methods. 3.- The publication of a letter paper in this prestigious journal requires that the proposed paper is practically free from any errors; however, please the following basic mistakes were directly found by this reviewer:

1. Before equation (1), a space is found between “follows” and “:”.
2. After equation (1), “M” appears in normal writing while in equation (1) is in italic typesetting.
3. After equation (2), it says: “where S is the symbol phase…”; but where is “S” in the equation?
4. In equation (7), the parameter alpha is introduced, but its meaning was not conveniently explained, as it has not the same meaning in [5].

As an overall conclusion, I suggest the authors to consider refocusing the paper in explaining the importance of the proposed embedded methodology and the use of the genetic algorithm for improving previous works based on rounding of reduced-Arc idea.

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