Scrambling For Video Surveillance
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This document proposes a method for preserving privacy in video surveillance by scrambling regions of interest (ROIs) in video sequences. It discusses scrambling quantized DCT or DWT coefficients in compressed video to conceal information in ROIs while maintaining understanding of the overall scene. The scrambling is flexible and reversible with a private key, has low computational complexity, and introduces minimal impact on video coding performance. Previous approaches are also summarized.
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Scrambling For Video Surveillance
- 1. Frédéric Dufaux and Touradj Ebrahimi Presents by Kobi Magnezi
- 2. Abstract — Problem: Preserving privacy in video surveillance — Solution: Scrambling regions of interest (ROI) in a video sequence. — Implementation: efficient solution based on transform-domain scrambling
- 3. Abstract — Real life: — MPEG-4 — Motion JPEG 2000 — Results: — Conceal information in ROI in the scene while providing with a good level of security — Scrambling is flexible – distortion can be adjusted — Small impact on coding performance and negligible computational complexity increase.
- 4. Motivation — Video surveillance systems are becoming ubiquitous. — Strategic places — Airports — Banks — Public transportation — Busy city centers. — Increase security but fear the loss of privacy — à slowing down the deployment of video surveillance.
- 5. George Orwell Big brother: “While tens of millions in government funding have been spent on research improving video surveillance, virtually none has been invested in technologies to enhance privacy or effectively balance privacy and security”
- 6. Architecture Wireless Wired
- 7. Architecture
- 8. Architecture ROI Scramble Compress •Face detections •Change Detection •Tracking •Skin detection Privacy Video •Object segmentation & tracking •Combination
- 9. 5 Previous approaches addressed privacy in video surveillance
- 10. Blinkering Surveillance: Enabling Video Privacy through Computer Vision. IBM Technical — “Just enoughquot; of the video stream — OO — PrivacyCam
- 11. Blinkering Surveillance: Enabling Video Privacy through Computer Vision. IBM Technical — Approach — OO representation of the scene — Re-render frames based on ACL — Technology — Privacy console that manages different versions of the video data based on ACL. — Privacy Cam - smart camera produces a video stream with the privacy-intrusive information already removed.
- 12. “The networked sensor tapestry (NeST): a privacy enhanced software architecture for interactive analysis of data in video-sensor networks — Networked Sensor Tapestry (NeST) Test-bed under development — Secure sharing — Capture — Distributing — Archiving — Architecture — Centralized server — Mobile hardware clients (TinyOS) — Layered XML messaging schema
- 13. “The networked sensor tapestry (NeST): a privacy enhanced software architecture for interactive analysis of data in video-sensor networks — Main concepts: — privacy buffer — privacy filters — privacy grammar — The utility of the architecture — variety of hardware/software clients — remote sensor interface device — software modules for sensor data — data visualization, sensor control — data archival applications
- 14. Preserving Privacy by De-identifying Facial Images — Algorithm to protect the privacy by de-identifying faces — Old approaches — Blacking out each face — covering eyes — randomly perturbing image pixels à fail for robustness of face recognition methods
- 15. Preserving Privacy by De-identifying Facial Images New approach - k-Same limits the ability of face recognition software. The algorithm • determines similarity between faces • creates new faces by averaging image components, • varying k.
- 16. Privacy through Invertible Cryptographic Obscuration — Scene distortion via cryptography — Encryption techniques to improve the privacy aspects Allowing full access Allowing general (i.e. violation of surveillance to privacy) only with use continue of a decryption key
- 17. Video surveillance using JPEG 2000 — JPEG 2000 compression — Events detection and ROI identification — Compressed video streams are scrambled and signed — Privacy — Data Integrity — Standards — JPSEC — JPWL
- 18. JPWL / JPSec Schema
- 19. Previous approaches with JPEG — The process — Identify ROI (people, privacy-sensitive info) — ROIs à Code-blocks — Code-blocks scrambled by ACL — Lowering quality layer of the codestream (bandwidth) — Drawback — Shape of the scrambled region is restricted to match code-block boundaries.
- 20. How we’ll make it better? — We want that — Scene remains understandable — The people are unidentifiable. — Security — private encryption key — Control who can unlock and view the whole scene in clear.
- 21. How we’ll make it better? — Output: single protected code-stream to all clients — No private key à distorted version of the content — Private key à unscramble the code-stream. — Can be used with — DCT-based: Motion JPEG, MPEG-4 or AVC 2x HD !! — DWT-based Motion JPEG 2000. 64 kBits 960 MBits — Goodies — Flexible Technique can be restricted to arbitrary-shape ROIs — Level of distortion (fuzzy to completely noisy)
- 24. Why Compress/Encode Video Source Output Data Rate[Kbits/sec] Quarter VGA @20 frames/sec 36 864.00 CIF camera @30 frames/sec 72 990.72 VGA @30 frames/sec 221 184.00 Transmission Medium Data Rate [Kbits/sec] Wireline modem 56 GPRS (estimated average rate) 30 3G/WCDMA (theoretical maximum) 384
- 25. MPEG-4 — Based on a motion compensation — Block-based DCT — Compression Predicted frames Intraframes
- 26. Four 8x8 Blocks for DCT 16x16 MacroBlocks
- 27. black with lot of change in frequency à DCT random matrix cosine function: horizontal, diagonal and vertical frequencies one color --> matrix with 1st large value & zeros
- 28. DCT cosine function: horizontal, diagonal and vertical frequencies Much of the signal energy lies at Low frequencies High frequencies. Often small to be neglected with a little distortion.
- 29. Human visual system experiments standard quantization matrix >50 less compress * (100-quality)/50 <50 more compress / lower quality * 50/quality
- 31. Quality factor of 75
- 32. Quality factor of 20
- 33. Quality factor of 5
- 34. Quality factor of 3
- 35. Entropy Encoder (Compress…) — Variable length Coding Huffman Coding or others…
- 36. Huffman Coding — The symbol with the highest probability is assigned the shortest code and vice versa. — Code words length is not fixed (VLC) — A codeword cannot be a prefix for another codeword (Self Synchronized Code)
- 37. Huffman Coding
- 39. Video Scrambling Earlier works Our approach — Traditional cryptographic — Bit scrambling techniques — Encrypt the compressed — Encrypt before compressing video. — Whole image completely — Whole scene remains distorted à indecipherable comprehensible but some objects cannot be identified — Coding performance — Complexity increase — Arbitrary-shape ROI — Flexible distortion
- 40. So when we scrambling? Before After Perform scrambling in the original Apply scrambling after encoding. (the image prior to encoding. compressed codestream is directly — Advantage: scrambled) Very simple and independent — Disadvantage: from the encoding scheme Very difficult to guarantee that the subsequently used. scrambled codestream will not — Disadvantage: crash a standard decoder. Significantly altering the statistics of the video signal, hence making the ensuing compression less efficient. Scrambling in the transform-domain. Region-based transform domain scrambling technique inverting the signs of selected transform coefficients
- 41. Transform-domain Scrambling — Frames transform using an energy compaction transform: DCT, DWT — The resulting coefficients are then entropy coded using techniques such as Huffman or arithmetic coding.
- 43. MPEG-4 & Scrambling — Effectively applied on the quantized DCT coefficients, and outside of the motion compensation loop
- 44. The scrambling recipe — What can be scrambled? — In general, DC coefficients are strongly correlated and are therefore unsuitable for scrambling. — Their signs are not.
- 45. The scrambling recipe — So what can be done? — All DC coefficients of the blocks corresponding to the ROIs are scrambled by pseudo-randomly flipping their sign.
- 46. The scrambling recipe — The shape of the scrambled region is restricted to match the 8x8 DCT blocks boundaries. — Level of scrambling = fewer AC coefficients.
- 48. Drifts… — Unauthorized decoder (not capable of unscrambling) will use a different motion compensation loop than an authorized decoder — Result: Unauthorized decoder may experience a drift, resulting in — artifacts in the scrambled sequence
- 49. How to avoid it? — Scrambled MB in the reference frame, are always INTRA coded. — Prevents the drift in motion compensation loop Predicted frames Intraframes
- 51. Encryption — PRNG initialized by a seed — SHA1PRNG with 64bit seed — Increase security à Multiple seed can be used — Seeds value encrypted using RSA — Inserted to the code-stream — Shape of ROI’s — Meta Data in MPEG-4 (private data / codestream) — Separate Channel
- 52. Complexity? — Flipping sings of selected coefficients
- 54. Scrambling — Effectively applied after the DWT and quantization, and before the arithmetic coder
- 55. De-Srambling — The process is fully reversible. At the decoder, authorized users have merely to perform the exact inverse operation.
- 56. Looks familiar? — Similar approach as proposed for MPEG-4 — Quantized wavelet coefficients are scrambled by pseudo randomly flipping their sign KM2 — Level of scrambling = fewer resolution levels.
- 57. Slide 56 ???? KM2 bandwith Kobi Magnezi, 10/06/2009
- 58. Goodies of JPEG2000 — The shape of the ROIs — Embedded ROI mechanism of JPEG 2000. — Leveraging standard JPEG security (JPSEC) — The seeds (for PRNG) can be encrypted and embedded in the codestream. à Fully JPSEC compliant.
- 60. Varying scrambling strength for MPEG-4
- 61. Varying scrambling strength for Motion HPEG 2000
- 62. Coding efficiency MPEG-4 Less than 10% bitrate increases
- 63. Coding efficiency Motion JPEG2000 Approximately 10% bitrate increases
- 65. Security Strength — Brute-force attack — tries all combinations reversing the signs of all non-zero AC coefficients. — CIF frame (352x288) — We consider the luminance component — MPEG-4 and Motion JPEG 2000 — à 99’792 AC coefficients. — ROI’s — Suppose that the attacker knows the ROIs which cover 5% of the image — à restricting the number of corresponding AC coefficients to 4’990. — Non-Zero — assuming that only 5 % of those are nonzero — Need to try reversing the signs of 250 coefficients à 2250 combinations for each frame. — à good level of security.
- 66. something to think about…
- 67. Eagle Eye