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Contribution of Non-Scrambled Chroma Information in
  Privacy-Protected Face Images to Privacy Leakage



10th International Workshop on Digital Forensics and Watermarking
                             October 2011


         Hosik Sohn1, Dohyoung Lee2, Wesley De Neve1,
         Konstantinos N. Plataniotis2, and Yong Man Ro1

   1Korea   Advanced Institute of Science and Technology (KAIST),
                   Image and Video Systems Lab
                       2University of Toronto,

                           Multimedia Lab
-2-


Contents

1. Introduction

2. Layered Scrambling for Motion JPEG XR

3. Assessment of Chroma-induced Privacy Leakage

   3.1 Objective Assessments

   3.2 Subjective Assessments

4. Discussion and Conclusions
-3-




INTRODUCTION
-4-


1. Introduction
 Present-day video surveillance systems often come with high-speed network
  connections, plenty of storage capacity, and high processing power

 The increasing ability of video surveillance systems to identify people has
  recently raised several privacy concerns

 To mitigate these privacy concerns, scrambling can be leveraged to conceal
  the identity of face images in video content originating from surveillance
  cameras




                             Privacy protected surveillance videos
-5-


1. Introduction

 The past few years have witnessed the development of a wide range of
  content-based tools for protecting privacy in video surveillance systems

     Dependent on the location where scrambling (or encryption) is applied, three
      different approaches of scrambling can be distinguished
         Uncompressed domain scrambling
         Transform domain scrambling
         Compressed bit stream domain scrambling


     One of the main challenges is the concealment of privacy-sensitive regions by
      making use of invertible transformation of visual information at a low
      computational cost
-6-


1. Introduction

 Content-based tools for privacy protection need to find a proper balance
  between the level of security offered and the amount of bit rate overhead
     In general, altering the visual information present in privacy-sensitive regions
      typically breaks the effectiveness of coding tools




                                                Coding
                             Security
                                               efficiency
                              level


 To limit the bit rate overhead, many content-based tools for privacy protection
  only scramble luma information, leaving chroma information unprotected
-7-


1. Introduction

 In this paper, we investigate the contribution of non-scrambled chroma
  information to privacy leakage

 To that end, we study and quantify the influence of the presence of non-
  scrambled chroma information on the effectiveness of automatic and human
  FR

     Objective assessment: we apply automatic FR techniques to face images that
      have been privacy-protected in the luma domain
     Subjective assessment: we investigate whether agreement exists between the
      judgments of 32 human observers and the output of automatic FR
-8-


      1. Introduction



       FR vs. perception-based security metrics for assessing the level of privacy

              Luminance Similarity Score (LSS), Edge Similarity Score (ESS), and Local
               Feature-based Visual Security Metric (LFVSM)[1,2]

              Note that these metrics are general in nature and are thus not able to take
               advantage of domain-specific information (e.g., face information)




[1] Tong, L., Dai, F., Zhang, Y., Li, J. “Visual security evaluation for video encryption,” in: Proceedings of ACM International Conference on
Multimedia, 835–838 (2010)
[2] Mao Y., Wu M., "A joint signal processing and cryptographic approach to multimedia encryption," IEEE Transactions on Image Processing,
15(7), 2061-2075 (2006)
-9-




LAYERED SCRAMBLING FOR
MOTION JPEG XR
-10-


      2. Layered Scrambling for Motion JPEG XR

       The video surveillance system studied makes use of Motion JPEG XR to
        encode surveillance video content
              Motion JPEG XR offers a low-complexity solution for the intra coding of high-resolution
               video content, while at the same time offering quality and spatial scalability provisions


       Layered scrambling for JPEG XR [3]
              Modified JPEG XR encoder
                                                                               Secret key
                                              DC subband
                                                                              Scrambling
                           LBT       LBT       Q      Pred.
                                                                                (RLS)         • Adaptive
                                              LP subband                                        entropy
                                                                Adaptive      Scrambling        coding
                                               Q      Pred.
                                                                 scan            (RP)         • Fixed
                                              HP subband/Flexbits                               length
                                                                Adaptive      Scrambling        coding
                                               Q      Pred.
                                                                 scan            (RSI)


[3] Sohn, H., De Neve, W., Ro, Y.M., “Privacy Protection in Video Surveillance Systems: Analysis of Subband-Adaptive Scrambling in JPEG
XR,” IEEE Transactions on Circuits and Systems for Video Technology, 21, 170–177 (2011)
-11-


2. Layered Scrambling for Motion JPEG XR

  Overview of the layered scrambling technique




                                                        - Random level shift (RLS) for DC subbands
                                                          DCcoeff e  DCcoeff  R(L),


                                                        - Random permutation (RP) for LP subbands

                                                         LPcoeffi e  LPcoeff j , where i  1,..., C, j  x1 ,..., xC ,


                                                        - Random sign inversion (RSI) for HP subbands
                                                                      HPcoeff , if r  1
                                                         HPcoeff e                       ,
                                                                      HPcoeff , otherwise


      N denotes the number of MBs, L denotes the RLS parameter, K denotes the number
       of non-zero LP coefficients in a MB, and M denotes the number of non-zero HP
       coefficients in a MB
-12-




ASSESSMENT OF CHROMA-INDUCED
PRIVACY LEAKAGE
-13-


3.1. Objective Assessments
 Experimental setup
    FR techniques used: PCA, FLDA, LBP
    Face images: 3070 frontal face images of 68 subjects from CMU PIE
     (68 gallery, 340 training, and 2662 probe face images)
           Probe face images represent privacy-protected face images that appear in video
            content originating from surveillance cameras
    Performance evaluation: Cumulative Match Characteristic (CMC) curve

    Notations
     Notation                            Explanation
     DC, LP, and HP                      DC, LP, and HP subband
     S3                                  DC+LP+HP
     S2                                  DC+LP
     S1                                  DC
     Subscripts (Y, Co, Cg)              Luma and chroma channels (Y, Co, and Cg)
     Prime (′)                           Scrambled image data
-14-


3.1. Objective Assessments
 Influence of distance measurement on FR effectiveness
     Distance metric: Euclidean, Mahalanobis, Cosine, and Chi-square distance




                                                           DE : Euclidean distance
                                                           DM : Mahalanobis distance
                                                           DC : Cosine distance
                                                           DH : Chi-square distance




     In the remainder of our experiments, we make use of the Euclidean distance metric for
      PCA- and FLDA-based FR, and the Chi-square distance metric for LBP-based FR
-15-


3.1. Objective Assessments
 Scrambled luma information
    Assumes that an adversary is not able to take advantage of the possible presence of
     non-scrambled chroma information in the privacy-protected probe face images
-16-


3.1. Objective Assessments

 Scrambled luma and non-scrambled chroma information
    We investigate whether layered scrambling is still effective when the
     scrambled luma channel and the non-scrambled chroma channels are
     simultaneously used for the purpose of automatic FR

    We assume that an adversary has access to the compressed bit stream
     structure, and thus to the non-scrambled chroma information

    We adopt feature-level fusion in order to take advantage of non-
     scrambled chroma information
-17-


3.1. Objective Assessments
 Scrambled luma and non-scrambled chroma information
-18-


3.1. Objective Assessments
 Non-scrambled chroma information
-19-


3.2. Subjective Assessments

 Experimental setup
    Number of observers: 32
    We presented three scrambled probe face images of different subjects to the
     human observers for each experimental condition
    Assessment method
        Human observers were asked to select the gallery face image that is most similar to
         the given probe face image
        Human observers were also able to study the probe face images at different zoom
         levels




                       Gallery face images used for the subjective assessments
-20-


3.2. Subjective Assessments
 Non-scrambled chroma information
-21-


3.2. Subjective Assessments
 Scrambled luma and non-scrambled chroma information
-22-




DISCUSSION & CONCLUSIONS
-23-


4. Discussion

 For video surveillance applications requiring a high level of privacy protection, both
  the luma and the chroma channels need to be scrambled
     At the cost of a higher bit rate overhead
 Layered scrambling for both the luma (Y) and the chroma channels (Co and Cg)
-24-


4. Discussion
 Bit rate overhead




 Security (ideal case)
     Sub-sampling decreases the level of privacy protection, given the lesser amount
      of data available for scrambling
     Total number of combinations required to break the protection of 10 MBs is
      reduced from 3.6×10722 (4:4:4) to 1.7×10360 (4:2:0)
-25-


5. Conclusions and Future Work

 This paper studied and quantified the influence of non-scrambled chroma infor-
  mation on the effectiveness of automatic and human FR

 Our results show that, when an adversary has access to the coded bit stream
  structure, the presence of non-scrambled chroma information may significantly
  contribute to privacy leakage

 For video surveillance applications requiring a high level of privacy protection, our
  results indicate that both luma and chroma information needs to be scrambled at the
  cost of an increase in bit rate overhead

 In order to compile a benchmark for privacy protection tools, future research will
  focus on identifying additional worst case scenarios
-26-




Thank you for your attention!
-27-


APPENDIX A
 Effectiveness of general-purpose visual security metrics
     Visual security metrics used
         Luminance Similarity Score (LSS), Edge Similarity Score (ESS), and Local Feature-
          based Visual Security Metric (LFVSM)
     The lower the values computed by the visual security metrics, the higher the
      visual security
-28-


APPENDIX B
 Paper of interest
     Sohn, H., De Neve, W., Ro, Y.M., “Privacy Protection in Video Surveillance
      Systems: Analysis of Subband-Adaptive Scrambling in JPEG XR,” IEEE
      Transactions on Circuits and Systems for Video Technology, 21, 170–177
      (2011)


 Book chapter of interest
     Sohn, H., Lee, D., De Neve, W., Plataniotis, K.N., Ro, Y.M., “An objective and
      subjective evaluation of content-based privacy protection of face images in
      video surveillance systems using JPEG XR,” Accepted for publication in
      Effective Surveillance for Homeland Security: Balancing Technology and
      Social Issues, CRC Press / Taylor & Francis, To be published in 2013


 IVY Lab video surveillance data set
     http://ivylab.kaist.ac.kr/demo/vs/dataset.htm

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Contribution of Non-Scrambled Chroma Information in Privacy-Protected Face Images to Privacy Leakage

  • 1. Contribution of Non-Scrambled Chroma Information in Privacy-Protected Face Images to Privacy Leakage 10th International Workshop on Digital Forensics and Watermarking October 2011 Hosik Sohn1, Dohyoung Lee2, Wesley De Neve1, Konstantinos N. Plataniotis2, and Yong Man Ro1 1Korea Advanced Institute of Science and Technology (KAIST), Image and Video Systems Lab 2University of Toronto, Multimedia Lab
  • 2. -2- Contents 1. Introduction 2. Layered Scrambling for Motion JPEG XR 3. Assessment of Chroma-induced Privacy Leakage 3.1 Objective Assessments 3.2 Subjective Assessments 4. Discussion and Conclusions
  • 4. -4- 1. Introduction  Present-day video surveillance systems often come with high-speed network connections, plenty of storage capacity, and high processing power  The increasing ability of video surveillance systems to identify people has recently raised several privacy concerns  To mitigate these privacy concerns, scrambling can be leveraged to conceal the identity of face images in video content originating from surveillance cameras Privacy protected surveillance videos
  • 5. -5- 1. Introduction  The past few years have witnessed the development of a wide range of content-based tools for protecting privacy in video surveillance systems  Dependent on the location where scrambling (or encryption) is applied, three different approaches of scrambling can be distinguished  Uncompressed domain scrambling  Transform domain scrambling  Compressed bit stream domain scrambling  One of the main challenges is the concealment of privacy-sensitive regions by making use of invertible transformation of visual information at a low computational cost
  • 6. -6- 1. Introduction  Content-based tools for privacy protection need to find a proper balance between the level of security offered and the amount of bit rate overhead  In general, altering the visual information present in privacy-sensitive regions typically breaks the effectiveness of coding tools Coding Security efficiency level  To limit the bit rate overhead, many content-based tools for privacy protection only scramble luma information, leaving chroma information unprotected
  • 7. -7- 1. Introduction  In this paper, we investigate the contribution of non-scrambled chroma information to privacy leakage  To that end, we study and quantify the influence of the presence of non- scrambled chroma information on the effectiveness of automatic and human FR  Objective assessment: we apply automatic FR techniques to face images that have been privacy-protected in the luma domain  Subjective assessment: we investigate whether agreement exists between the judgments of 32 human observers and the output of automatic FR
  • 8. -8- 1. Introduction  FR vs. perception-based security metrics for assessing the level of privacy  Luminance Similarity Score (LSS), Edge Similarity Score (ESS), and Local Feature-based Visual Security Metric (LFVSM)[1,2]  Note that these metrics are general in nature and are thus not able to take advantage of domain-specific information (e.g., face information) [1] Tong, L., Dai, F., Zhang, Y., Li, J. “Visual security evaluation for video encryption,” in: Proceedings of ACM International Conference on Multimedia, 835–838 (2010) [2] Mao Y., Wu M., "A joint signal processing and cryptographic approach to multimedia encryption," IEEE Transactions on Image Processing, 15(7), 2061-2075 (2006)
  • 10. -10- 2. Layered Scrambling for Motion JPEG XR  The video surveillance system studied makes use of Motion JPEG XR to encode surveillance video content  Motion JPEG XR offers a low-complexity solution for the intra coding of high-resolution video content, while at the same time offering quality and spatial scalability provisions  Layered scrambling for JPEG XR [3]  Modified JPEG XR encoder Secret key DC subband Scrambling LBT LBT Q Pred. (RLS) • Adaptive LP subband entropy Adaptive Scrambling coding Q Pred. scan (RP) • Fixed HP subband/Flexbits length Adaptive Scrambling coding Q Pred. scan (RSI) [3] Sohn, H., De Neve, W., Ro, Y.M., “Privacy Protection in Video Surveillance Systems: Analysis of Subband-Adaptive Scrambling in JPEG XR,” IEEE Transactions on Circuits and Systems for Video Technology, 21, 170–177 (2011)
  • 11. -11- 2. Layered Scrambling for Motion JPEG XR  Overview of the layered scrambling technique - Random level shift (RLS) for DC subbands DCcoeff e  DCcoeff  R(L), - Random permutation (RP) for LP subbands LPcoeffi e  LPcoeff j , where i  1,..., C, j  x1 ,..., xC , - Random sign inversion (RSI) for HP subbands  HPcoeff , if r  1 HPcoeff e   ,  HPcoeff , otherwise  N denotes the number of MBs, L denotes the RLS parameter, K denotes the number of non-zero LP coefficients in a MB, and M denotes the number of non-zero HP coefficients in a MB
  • 13. -13- 3.1. Objective Assessments  Experimental setup  FR techniques used: PCA, FLDA, LBP  Face images: 3070 frontal face images of 68 subjects from CMU PIE (68 gallery, 340 training, and 2662 probe face images)  Probe face images represent privacy-protected face images that appear in video content originating from surveillance cameras  Performance evaluation: Cumulative Match Characteristic (CMC) curve  Notations Notation Explanation DC, LP, and HP DC, LP, and HP subband S3 DC+LP+HP S2 DC+LP S1 DC Subscripts (Y, Co, Cg) Luma and chroma channels (Y, Co, and Cg) Prime (′) Scrambled image data
  • 14. -14- 3.1. Objective Assessments  Influence of distance measurement on FR effectiveness  Distance metric: Euclidean, Mahalanobis, Cosine, and Chi-square distance DE : Euclidean distance DM : Mahalanobis distance DC : Cosine distance DH : Chi-square distance  In the remainder of our experiments, we make use of the Euclidean distance metric for PCA- and FLDA-based FR, and the Chi-square distance metric for LBP-based FR
  • 15. -15- 3.1. Objective Assessments  Scrambled luma information  Assumes that an adversary is not able to take advantage of the possible presence of non-scrambled chroma information in the privacy-protected probe face images
  • 16. -16- 3.1. Objective Assessments  Scrambled luma and non-scrambled chroma information  We investigate whether layered scrambling is still effective when the scrambled luma channel and the non-scrambled chroma channels are simultaneously used for the purpose of automatic FR  We assume that an adversary has access to the compressed bit stream structure, and thus to the non-scrambled chroma information  We adopt feature-level fusion in order to take advantage of non- scrambled chroma information
  • 17. -17- 3.1. Objective Assessments  Scrambled luma and non-scrambled chroma information
  • 18. -18- 3.1. Objective Assessments  Non-scrambled chroma information
  • 19. -19- 3.2. Subjective Assessments  Experimental setup  Number of observers: 32  We presented three scrambled probe face images of different subjects to the human observers for each experimental condition  Assessment method  Human observers were asked to select the gallery face image that is most similar to the given probe face image  Human observers were also able to study the probe face images at different zoom levels Gallery face images used for the subjective assessments
  • 20. -20- 3.2. Subjective Assessments  Non-scrambled chroma information
  • 21. -21- 3.2. Subjective Assessments  Scrambled luma and non-scrambled chroma information
  • 23. -23- 4. Discussion  For video surveillance applications requiring a high level of privacy protection, both the luma and the chroma channels need to be scrambled  At the cost of a higher bit rate overhead  Layered scrambling for both the luma (Y) and the chroma channels (Co and Cg)
  • 24. -24- 4. Discussion  Bit rate overhead  Security (ideal case)  Sub-sampling decreases the level of privacy protection, given the lesser amount of data available for scrambling  Total number of combinations required to break the protection of 10 MBs is reduced from 3.6×10722 (4:4:4) to 1.7×10360 (4:2:0)
  • 25. -25- 5. Conclusions and Future Work  This paper studied and quantified the influence of non-scrambled chroma infor- mation on the effectiveness of automatic and human FR  Our results show that, when an adversary has access to the coded bit stream structure, the presence of non-scrambled chroma information may significantly contribute to privacy leakage  For video surveillance applications requiring a high level of privacy protection, our results indicate that both luma and chroma information needs to be scrambled at the cost of an increase in bit rate overhead  In order to compile a benchmark for privacy protection tools, future research will focus on identifying additional worst case scenarios
  • 26. -26- Thank you for your attention!
  • 27. -27- APPENDIX A  Effectiveness of general-purpose visual security metrics  Visual security metrics used  Luminance Similarity Score (LSS), Edge Similarity Score (ESS), and Local Feature- based Visual Security Metric (LFVSM)  The lower the values computed by the visual security metrics, the higher the visual security
  • 28. -28- APPENDIX B  Paper of interest  Sohn, H., De Neve, W., Ro, Y.M., “Privacy Protection in Video Surveillance Systems: Analysis of Subband-Adaptive Scrambling in JPEG XR,” IEEE Transactions on Circuits and Systems for Video Technology, 21, 170–177 (2011)  Book chapter of interest  Sohn, H., Lee, D., De Neve, W., Plataniotis, K.N., Ro, Y.M., “An objective and subjective evaluation of content-based privacy protection of face images in video surveillance systems using JPEG XR,” Accepted for publication in Effective Surveillance for Homeland Security: Balancing Technology and Social Issues, CRC Press / Taylor & Francis, To be published in 2013  IVY Lab video surveillance data set  http://ivylab.kaist.ac.kr/demo/vs/dataset.htm