PONE-D-20-01807

Detecting face presentation attacks in mobile devices with a patch-based CNN and a sensor-aware loss function

PLOS ONE

Dear Dr. Andalo,

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He Debiao

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: N/A

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Strengths:

1)Authors have efficiently used SqueezeNet as the base of the training model which has around 1.2 million parameters that takes only 5MB of memory which is very suitable for a mobile device to operate.

2)The model structure is fully convolutional which made the input size and alignment much flexible and more accurate than AlexNet. All feature maps are flexible in size, but they kept the input shape as 3 x 227 x 227. And that gives one important flexibility. Scaling-down the pixels of the images does not lose much localisation information, rather it lets us free from taking long time to train the model.

3)Authors used variable resolution face-patches of the images. They claimed that it reduces overfitting to user-specific characteristics. And thus the learning becomes more robust as the images does not remain tied to any single scale anymore.

4)Through the experiment they found out that the camera specifications are very important here and while building the model this should be considered to avoid ending up with a biased model. And to overcome this problem, they came up with triplet-loss which also can be called intra-device triplet loss and spoof-loss which also can be called multi-objective loss instead of traditional cross-entropy loss.

5)Authors expressed their experiment result using 5 common considered biometric presentation attack evaluation namely Attack Presentation Classification Error Rate (APCER), Bona fide Presentation Classification Error Rate (BPCER), Average Classification Error Rate (ACER), Half-total Error Rate (HTER) and Equal Error Rate (EER). This made their experiment much stronger.

Weaknesses:

1)In the datasets authors have used, the devices were used are a little old version. The latest phone they have used Moto G5 was released in 2017. But in those phones there was no face detection technology. Rather face detection technologies are provided in the phones those were released very recently and obviously cameras on those phone are different. So those new phones like iphone 10, 11, galaxy s10 etc should have been given priority to acquire data. Also iPad should have been included in the device list.

2)Authors didn’t mentioned about gender or racial diversity in the dataset. There should have been a proper diversity ratio in the dataset.

3)Authors should have shown not only images but how video streams performs with this model.

4)Authors should have shown what properties of other CNN structures are failing in mobile device environment while SqueezeNet architecture is winning the situation with proper use-cases and example situations.

5)The main idea of this experiment was to differentiate between genuine access images and fake attack images. But ideally this experiment can be done not only on face images rather on images of other materials. They could show some results of experiments on the images other than face.

Reviewer #2: This paper presents a CNN-based algorithm to detect face presentation attacks, specifically for mobile devices. The idea is to use patches of varying resolution. This not only increases the number of available examples but also solves the overfitting issues. The authors also introduce a multi-objective loss function to reduce inter-device confusion. A comprehensive evaluation has been conducted on RECOD-MPAD, a new dataset tailored to the mobile-device setup. The results show that the proposed method achieves better results compared with state-of-the-art solutions.

Strength:

1: The paper is clearly written and well structured.

2: A new dataset is developed. It will be great if the authors can make it publicly available.

3: Evaluation is comprehensive and well justified.

Weakness:

Novelty is somehow limited. My understanding is that the authors merely apply the existing SqueezeNet architecture to the mobile scenario.

The authors claim that the dataset will be made available along with the article publication. It cannot be verified at the review stage.

Minor:

Page 2 line 42 - 49: missing section numbers.

Page 6 line 220 - 223: missing section numbers.

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Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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PONE-D-20-01807R1

Detecting face presentation attacks in mobile devices with a patch-based CNN and a sensor-aware loss function

PLOS ONE

Dear Dr. Andalo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Aug 10 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

He Debiao

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: N/A

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have addressed all comments satisfactorily. I recommend acceptance. This could be an important paper in the community of computer vision and security.

Reviewer #2: Thanks the authors for the contribution clarification.

Another concern I have after reading the revision is that the technique proposed in the paper is limited to images captured by traditional cameras. However, with the development of new technologies, such as face ID, which creates a depth map of faces and also captures an infrared image, the proposed approach will soon be obsolete. There is no doubt that new hardware can achieve better accuracy and privacy. The authors can argue that the proposed approach can be used in low-end smartphone. Other than that, could the authors provide any other insights?

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Detecting face presentation attacks in mobile devices with a patch-based CNN and a sensor-aware loss function

PONE-D-20-01807R2

Dear Dr. Andalo,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

He Debiao

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors address all concerns. The paper is recommended for acceptance. The response from the authors is thorough.

Reviewer #2: The authors have addressed all my concerns, including the discussion of advanced sensors and the release of the dataset. I recommend acceptance.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No