Managing Privacy Data in Camera Networks - Protecting Information efficiently
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Learn about a system overview and a three-agent architecture framework for reversible data hiding to preserve privacy data securely. Explore the results, future work, and privacy protection techniques for efficient management of privacy information.
Managing Privacy Data in Camera Networks - Protecting Information efficiently
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Managing Privacy Data in Pervasive Camera Networks Jithendra K. Paruchuri Department of ECE University of Kentucky Lexington, KY - 40508 Thinh P. Nguyen Department of EECS Oregon State University Corvallis, OR - 97330 Sen-ching S. Cheung Department of ECE University of Kentucky Lexington, KY - 40508 ICIP Oct 14 2008
Outline • Motivation and Problem • System Overview • Three Agent Architecture • Reversible Data Hiding Framework • Results • Conclusion & Future Work www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Privacy in Pervasive Camera Networks www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Client A Client B Client C Privacy Protection Privacy Data Flow Subject A Privacy Data Management System Subject B Subject C Key question 1: How does a client know which subject to ask? Key question 2: How to manage the privacy information in a secure and efficient manner? www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Contributions • Retrieval of Privacy Data • Software Agents Architecture • Efficient : No video data exchange • Robustness: No states in agents • Security: No centralized server • Privacy Data Preservation • Reversible Data-Hiding in Compressed Domain • R-D optimized Embedding www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Outline • Motivation and Problem • System Overview • Three Agent Architecture • Reversible Data Hiding Framework • Results • Conclusion & Future Work www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Privacy Protecting System RFID Tracking System Key Generation Camera System Object Identification Encryption Object Removal & Obfuscation Data Hiding Video Database Mediator Agent Request Request Permission Permission Client Agent Subject Agent www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Outline • Motivation and Problem • System Overview • Three Agent Architecture • Reversible Data Hiding Framework • Results • Conclusion & Future Work www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Step 3 S RSA(K; PKS) TOC: RSA(K;PKC) RSA(K;PKC) Step 6 Step 7 RSA(K; PKC) Step 5 Three Agent Architecture Mediator Agent PKM,SKM Step 2 Step 1 Step 4 Client’s Request S S RSA(K; PKS) RSA(K; PKS) RSA(K; PKS) RSA(TOC; PKm) RSA(TOC; PKm) AES(VS; K) • • • • Subject Agent PKS,SKS Client Agent PKC,SKC AES(VS; K)
Outline • Motivation and Problem • System Overview • Three Agent Architecture • Reversible Data Hiding Framework • Results • Conclusion & Future Work www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Privacy Data Preservation • Cryptographic Scrambling [Boult05], [Dufaux06] • Data Hiding in DCT [Zhang05] • Joint Optimization of Data Hiding & Video Compression [Paruchuri08]
Parity Embedding Last decoded frame DCT Perceptual Mask • DCT Domain • Frequency, contrast and • luminance masking [Watson] Data Hiding with Compression DCT Entropy Coding Motion Compensation www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
R-D optimized Data Hiding Parity Embedding Last decoded frame Positions of the “optimal’ DCT coeff for embedding DCT R-D Optimization Perceptual Mask • DCT Domain • Frequency, contrast and • luminance masking [Watson] DCT Entropy Coding Reversible Embedding Motion Compensation H.263 H.263 www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Reversible Embedding • Authentication: Authorized decoder can perfectly reverse image modifications • Problem with Motion loop • Original reference frame unavailable to regular decoder • Hidden data included in feedback loop • Irreversible effect after quantization • Use Motion-JPEG instead
Reversible Embedding [Ni et al. 03] DCT Residue Histogram • Embedding only at zero location • DCT Residue is Laplacian distributed
Combined rate- distortion cost C(x) # embedded bits R-D based Data Hiding Block-based Rate-Distortion Calculation Psycho-visual Model in DCT [Watson 93] Embedded bit allocation among DCT blocks Solve constrained optimization
Constrained Optimization Let Rk(Mk) and Dk(Mk) be the rate and distortion after hiding Mk bits into the k-th DCT block. δ is a user-defined weight Optimization Problem:
Calculations of Rk(Mk) and Dk(Mk) • Two Issues: • Parity embedding depends on hidden data • Need to find optimal selection within block • “Worst-case” embedding on previous frame • Optimal selection • Complicated by run-length coding • Fast: high to low frequency embedding • Slow: Greedy optimization within block • Very slow: Exhaustive search with DP
Dual of the optimization • Lower bounded by unconstrained opt: • Search λ to meet constraint • Start at 2nd order approximation of Ck(Mk) • 3-5 seconds per one CIF frame
Outline • Motivation and Problem • System Overview • Three Agent Architecture • Reversible Data Hiding Framework • Results • Conclusion & Future Work www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Hall Monitor (QP=10) - MJPEG www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Hall Monitor (QP=10) Original Distortion Optimized Weight = 0.5 Rate Optimized
Hall Monitor vs. QP at δ = 0.5 www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Outline • Motivation and Problem • System Overview • Three Agent Architecture • Reversible Data Hiding Framework • Results • Conclusion & Future Work www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257
Conclusions • Privacy System framework • Privacy Data Management Architecture • Privacy Data Preservation by Data Hiding • Current work • Reversible Data Embedding for Scalable Video • Distributed Architecture Privacy Data Management • Incorporate temporal dimension in perceptual and rate model • Perceptual evaluation www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257