Pinto: Enabling Video Privacy for Commodity IoT Cameras

With various IoT cameras today, sharing of their video evidences, while benefiting the public, threatens the privacy of individuals in the footage. However, protecting visual privacy without losing video authenticity is challenging. The conventional post-process blurring would open the door for posterior fabrication, whereas the realtime blurring results in poor quality, low-frame-rate videos due to the limited processing power of commodity cameras. This paper presents Pinto, a software-based solution for producing privacy-protected, forgery-proof, and high-frame-rate videos using low-end IoT cameras. Pinto records a realtime video stream at a fast rate and allows post-processing for privacy protection prior to sharing of videos while keeping their original, realtime signatures valid even after the post blurring, guaranteeing no content forgery since the time of their recording. Pinto is readily implementable in today's commodity cameras. Our prototype on three different embedded devices, each deployed in a specific application context---on-site, vehicular, and aerial surveillance---demonstrates the production of privacy-protected, forgery-proof videos with frame rates of 17--24 fps, comparable to those of HD videos.

[1]  Alexandros André Chaaraoui,et al.  Visual privacy protection methods: A survey , 2015, Expert Syst. Appl..

[2]  Feng Gu,et al.  Visual Privacy by Context: Proposal and Evaluation of a Level-Based Visualisation Scheme , 2015, Sensors.

[3]  Prashasti Kanikar,et al.  Pixel Based Digital Image Forgery Detection Techniques , 2012 .

[4]  Christian Damsgaard Jensen,et al.  Video Surveillance: Privacy Issues and Legal Compliance , 2015 .

[5]  Ralph Gross,et al.  Face De-identification , 2009, Protecting Privacy in Video Surveillance.

[6]  Janarbek Matai,et al.  Design and Implementation of an FPGA-Based Real-Time Face Recognition System , 2011, 2011 IEEE 19th Annual International Symposium on Field-Programmable Custom Computing Machines.

[7]  Jessica Fridrich,et al.  Detection of Copy-Move Forgery in Digital Images , 2004 .

[8]  Ingemar J. Cox,et al.  Digital Watermarking and Steganography. Ed.2 , 2019 .

[9]  Sotiris Ioannidis,et al.  Face/Off: Preventing Privacy Leakage From Photos in Social Networks , 2015, CCS.

[10]  Angelos Stavrou,et al.  Privacy Risk Assessment on Online Photos , 2015, RAID.

[11]  Julie E. Cohen Privacy, Visibility, Transparency, and Exposure , 2007 .

[12]  Aakanksha Chowdhery,et al.  The Design and Implementation of a Wireless Video Surveillance System , 2015, MobiCom.

[13]  Bradley Malin,et al.  Preserving privacy by de-identifying face images , 2005, IEEE Transactions on Knowledge and Data Engineering.

[14]  Hany Farid,et al.  Detecting Photographic Composites of People , 2008, IWDW.

[15]  Ricardo L. de Queiroz,et al.  Identification of bitmap compression history: JPEG detection and quantizer estimation , 2003, IEEE Trans. Image Process..

[16]  Jing Zhang,et al.  A new approach for detecting Copy-Move forgery in digital images , 2008, 2008 11th IEEE Singapore International Conference on Communication Systems.

[17]  Adam Finkelstein,et al.  Robust mesh watermarking , 1999, SIGGRAPH.

[18]  Ratul Mahajan,et al.  sTrack: Secure Tracking in Community Surveillance , 2014, ACM Multimedia.

[19]  Anita Sahani,et al.  Image Forgery Detection Using Svm Classifier , 2014 .

[20]  Pan Hui,et al.  Cardea: Context-Aware Visual Privacy Protection from Pervasive Cameras , 2016, ArXiv.

[21]  H. Farid,et al.  Image forgery detection , 2009, IEEE Signal Processing Magazine.

[22]  Yuewei Dai,et al.  A Fast Image Copy-Move Forgery Detection Method Using Phase Correlation , 2012, 2012 Fourth International Conference on Multimedia Information Networking and Security.

[23]  N. Sudha,et al.  Verifying Temporal Data in Geotagged Images Via Sun Azimuth Estimation , 2012, IEEE Transactions on Information Forensics and Security.

[24]  Song Wang,et al.  Are You Lying: Validating the Time-Location of Outdoor Images , 2017, ACNS.

[25]  Edward J. Delp,et al.  Fragile watermarking using the VW2D watermark , 1999, Electronic Imaging.

[26]  A. Sheikholeslami,et al.  Real-time face detection and lip feature extraction using field-programmable gate arrays , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[27]  Nasir Shaikh-Husin,et al.  Hardware acceleration of a face detection system on FPGA , 2015, 2015 IEEE Student Conference on Research and Development (SCOReD).

[28]  C. Mala,et al.  Comparative Study of Image Forgery and Copy-Move Techniques , 2012 .

[29]  Jonathan Rose,et al.  Real-time, frame-rate face detection on a configurable hardware system (poster abstract) , 2000, FPGA '00.

[30]  Deepa Kundur,et al.  Video fingerprinting and encryption principles for digital rights management , 2004, Proceedings of the IEEE.

[31]  Ryan Kastner,et al.  Fpga-based face detection system using Haar classifiers , 2009, FPGA '09.

[32]  Mauro Barni,et al.  A DCT-domain system for robust image watermarking , 1998, Signal Process..

[33]  Edoardo M. Airoldi,et al.  Integrating Utility into Face De-identification , 2005, Privacy Enhancing Technologies.

[34]  K V.P.,et al.  A Novel Digital Image Forgery Detection Method Using SVM Classifier , 2014 .

[35]  M. Angela Sasse,et al.  Sharp or smooth?: comparing the effects of quantization vs. frame rate for streamed video , 2004, CHI '04.

[36]  Younghoon Kim,et al.  ViewMap: Sharing Private In-Vehicle Dashcam Videos , 2017, NSDI.

[37]  Jan Lukás,et al.  Estimation of Primary Quantization Matrix in Double Compressed JPEG Images , 2003 .

[38]  Scott B. Baden,et al.  Accelerating Viola-Jones Face Detection to FPGA-Level Using GPUs , 2010, 2010 18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines.

[39]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[40]  C. F. Osborne,et al.  A digital watermark , 1994, Proceedings of 1st International Conference on Image Processing.

[41]  Carlisle M. Adams,et al.  Internet X.509 Public Key Infrastructure Time-Stamp Protocol (TSP) , 2001, RFC.

[42]  H. Farid Image Forgery Detection -- A survey , 2009 .

[43]  Anindya Sarkar,et al.  Video fingerprinting: features for duplicate and similar video detection and query-based video retrieval , 2008, Electronic Imaging.

[44]  David J. Crandall,et al.  Viewer Experience of Obscuring Scene Elements in Photos to Enhance Privacy , 2018, CHI.

[45]  Ratul Mahajan,et al.  Bolt: Data Management for Connected Homes , 2014, NSDI.

[46]  Ratul Mahajan,et al.  Digital neighborhood watch: investigating the sharing of camera data amongst neighbors , 2013, CSCW.

[47]  Ingemar J. Cox,et al.  Digital Watermarking and Steganography , 2014 .