ABSTRACT
The ubiquity of portable mobile devices equipped with built-in cameras have led to a transformation in how and when digital images are captured, shared, and archived. Photographs and videos from social gatherings, public events, and even crime scenes are commonplace online. While the spontaneity afforded by these devices have led to new personal and creative outlets, privacy concerns of bystanders (and indeed, in some cases, unwilling subjects) have remained largely unaddressed. We present I-Pic, a trusted software platform that integrates digital capture with user-defined privacy. In I-Pic, users choose alevel of privacy (e.g., image capture allowed or not) based upon social context (e.g., out in public vs. with friends vs. at workplace). Privacy choices of nearby users are advertised via short-range radio, and I-Pic-compliant capture platforms generate edited media to conform to privacy choices of image subjects. I-Pic uses secure multiparty computation to ensure that users' visual features and privacy choices are not revealed publicly, regardless of whether they are the subjects of an image capture. Just as importantly, I-Pic preserves the ease-of-use and spontaneous nature of capture and sharing between trusted users. Our evaluation of I-Pic shows that a practical, energy-efficient system that conforms to the privacy choices of many users within a scene can be built and deployed using current hardware.
- Lost lake cafe, seattle restaurant, kicks out patron for wearing google glass. http://www.huffingtonpost.com/2013/11/27/lost-lake-cafe-google-glass_n_4350039.html.Google Scholar
- Franziska Roesner, David Molnar, Alexander Moshchuk, Tadayoshi Kohno, and Helen J. Wang. World-driven access control for continuous sensing. In ACM Conference on Computer and Communications Security (CCS), 2014. Google ScholarDigital Library
- Nisarg Raval, Animesh Srivastava, Ali Razeen, Kiron Lebeck, Ashwin Machanavajjhala, and Landon P. Cox. What you mark is what apps see. In ACM International Conference on Mobile Systems, Applications, and Services (Mobisys), 2016. Google ScholarDigital Library
- Cheng Bo, Guobin Shen, Jie Liu, Xiang-Yang Li, Yongguang Zhang, and Feng Zhao. Privacy.tag: Privacy concern expressed and respected. In ACM Conference on Embedded Networked Sensor Systems (Sensys), 2014. Google ScholarDigital Library
- Nisarg Raval, Animesh Srivastava, Kiron Lebeck, Landon P. Cox, and Ashwin Machanavajjhala. Markit: Privacy markers for protecting visual secrets. In UPSIDE, Workshop at ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp), 2014. Google ScholarDigital Library
- M. Mathias, R. Benenson, M. Pedersoli, and L. Van Gool. Face detection without bells and whistles. In European Conference on Computer Vision (ECCV), 2014.Google ScholarCross Ref
- S. Joon Oh, R. Benenson, M. Fritz, and B. Schiele. Person recognition in personal photo collections. In International Conference on Computer Vision (ICCV), 2015. Google ScholarDigital Library
- Bart Goethals, Sven Laur, Helger Lipmaa, and Taneli Mielikainen. On private scalar product computation for privacy-preserving data mining. In 7th Annual International Conference in Information Security and Cryptology (ICISC), 2004. Google ScholarDigital Library
- Andrew Chi-Chih Yao. How to generate and exchange secrets. In 27th Annual Symposium on Foundations of Computer Science (FOCS), 1986. Google ScholarDigital Library
- Terence Sim and Li Zhang. Controllable face privacy. In The 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), 2015.Google Scholar
- Antonio Criminisi, Patrick Perez, and Kentaro Toyama. Region filling and object removal by exemplar-based image inpainting. In IEEE Transactions on image processing, vol. 13, no. 9, September, 2004. Google ScholarDigital Library
- X. Zhu and D. Ramanan. Face detection, pose estimation and landmark localization in the wild. In Computer Vision and Pattern Recognition (CVPR), 2012. Google ScholarDigital Library
- Ning Zhang, Manohar Paluri, Yaniv Taigman, Rob Fergus, and Lubomir Bourdev. Beyond frontal faces: Improving person recognition using multiple cues. In Conference on Computer Vision and Pattern Recognition (CVPR), 2015.Google ScholarCross Ref
- A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In Conference on Neural Information Processing Systems (NIPS). 2012.Google Scholar
- J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. ImageNet: A Large-Scale Hierarchical Image Database. Computer Vision and Pattern Recognition (CVPR), 2009.Google ScholarCross Ref
- Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell. Caffe: Convolutional architecture for fast feature embedding. arXiv preprint arXiv:1408.5093, 2014.Google Scholar
- Gary B. Huang Erik Learned-Miller. Labeled faces in the wild: Updates and new reporting procedures. Technical Report UM-CS-2014-003, University of Massachusetts, Amherst, May 2014.Google Scholar
- Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin. LIBLINEAR: A library for large linear classification. Journal of Machine Learning Research, 2008. Google ScholarDigital Library
- Pascal Paillier. Public-key cryptosystems based on composite degree residuosity classes. In Advances in Cryptology (EUROCRYPT), 1999. Google ScholarDigital Library
- Paarijaat Aditya et al. Technical Report: I-Pic: A Platform for Privacy-Compliant Image Capture. http://www.mpi-sws.org/ paditya/papers/ipic-tr.pdf.Google Scholar
- Yan Huang, Lior Malka, David Evans, and Jonathan Katz. Efficient privacy-preserving biometric identification. In 18th Network and Distributed System Security Conference (NDSS), 2011.Google Scholar
- Moni Naor and Benny Pinkas. Computationally secure oblivious transfer. In Journal of Cryptology, 2005. Google ScholarDigital Library
- Yuval Ishai, Joe Kilian, Kobbi Nissim, and Erez Petrank. Extending oblivious transfers efficiently. In Advances in Cryptology (CRYPTO), 2003.Google ScholarCross Ref
- Yehuda Lindell. Fast cut-and-choose based protocols for malicious and covert adversaries. In Advances in Cryptology (CRYPTO), 2013.Google ScholarCross Ref
- Project Tango Tablet Development Kit. https://store.google.com/product/project_tango_tablet_development_kit.Google Scholar
- CUDA. http://www.nvidia.com/object/cuda_home_new.html.Google Scholar
- Jose-Luis Lisani, Ana-Belen Petro, and Catalina Sbert. Color and Contrast Enhancement by Controlled Piecewise Affine Histogram Equalization. Image Processing On Line, 2:243--265, 2012. http://dx.doi.org/10.5201/ipol.2012.lps-pae.Google ScholarCross Ref
- Caffe-Android-Lib. https://github.com/sh1r0/caffe-android-lib.Google Scholar
- Might Be Evil. http://mightbeevil.org/.Google Scholar
- A universal labeling tool: Sloth. https://cvhci.anthropomatik.kit.edu/ baeuml/projects/a-universal-labeling-tool-for-computer-vision-sloth/.Google Scholar
- Monsoon Power Monitor. https://www.msoon.com/LabEquipment/PowerMonitor.Google Scholar
- Nvidia. Nvidia Shield Tablet K1. https://shield.nvidia.com/tablet/k1.Google Scholar
- Roberto Hoyle, Robert Templeman, Steven Armes, Denise Anthony, David Crandall, and Apu Kapadia. Privacy behaviors of lifeloggers using wearable cameras. In ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp), 2014. Google ScholarDigital Library
- Tamara Denning, Zakariya Dehlawi, and Tadayoshi Kohno. In situ with bystanders of augmented reality glasses: Perspectives on recording and privacy-mediating technologies. In ACM Conference on Human Factors in Computing Systems (CHI), 2014. Google ScholarDigital Library
- Jaeyeon Jung and Matthai Philipose. Courteous glass. In UPSIDE, Workshop at ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp), 2014. Google ScholarDigital Library
- Loris D'Antoni, Alan Dunn, Suman Jana, Tadayoshi Kohno, Benjamin Livshits, David Molnar, Alexander Moshchuk, Eyal Ofek, Franziska Roesner, Scott Saponas, Margus Veanes, and Helen J. Wang. Operating system support for augmented reality applications. In Workshop on Hot Topics in Operating Systems (HotOS), 2013. Google ScholarDigital Library
- Suman Jana, Arvind Narayanan, and Vitaly Shmatikov. A scanner darkly: Protecting user privacy from perceptual applications. In IEEE Symposium on Security and Privacy, 2013. Google ScholarDigital Library
- Suman Jana, David Molnar, Alexander Moshchuk, Alan Dunn, Benjamin Livshits, Helen J. Wang, and Eyal Ofek. Enabling fine-grained permissions for augmented reality applications with recognizers. In Usenix Security Symposium (Usenix Security), 2013. Google ScholarDigital Library
- Christopher Smowton, Jacob R. Lorch, David Molnar, Stefan Saroiu, and Alec Wolman. Zero-effort payments: Design, deployment, and lessons. In Proceedings of the ACM International Joint Conference on Pervasive and UbiquitousComputing (UbiComp), 2014. Google ScholarDigital Library
- Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, and Lior Wolf. Deepface: Closing the gap to human-level performance in face verification. In Conference on Computer Vision and Pattern Recognition (CVPR), 2014. Google ScholarDigital Library
- Lubomir Bourdev, Subhransu Maji, and Jitendra Malik. Describing people: Poselet-based attribute classification. In International Conference on Computer Vision (ICCV), 2011. Google ScholarDigital Library
- Ning Zhang, Manohar Paluri, Marc'Aurelio Ranzato, Trevor Darrell, and Lubomir D. Bourdev. PANDA: pose aligned networks for deep attribute modeling. In Conference on Computer Vision and Pattern Recognition (CVPR), 2014. Google ScholarDigital Library
- Zhou Lingli and Lai Jianghuang. Security algorithm of face recognition based on local binary pattern and random projection. In International Conference on Computational Intelligence (ICCI), 2010.Google ScholarCross Ref
- Yongjin Wang and Konstantinos N. Plataniotis. An analysis of random projection for changeable and privacy-preserving biometric verification. IEEE Transactions on Systems, Man, and, Cybernetics: part B: CYBERNETICS, Vol. 40, No. 5, 2010. Google ScholarDigital Library
- Per Hallgren, Martin Ochoa, and Andrei Sabelfeld. Innercircle: A parallelizable decentralized privacy-preserving location proximity protocol. In Proceedings of the 13th Annual Conference on Privacy, Security and Trust (PST), 2015.Google ScholarCross Ref
Index Terms
- I-Pic: A Platform for Privacy-Compliant Image Capture
Recommendations
EnCore: private, context-based communication for mobile social apps
MobiSys '14: Proceedings of the 12th annual international conference on Mobile systems, applications, and servicesMobile social apps provide sharing and networking opportunities based on a user's location, activity, and set of nearby users. A platform for these apps must meet a wide range of communication needs while ensuring users' control over their privacy. In ...
Fine-Grained Cloaking of Sensitive Positions in Location-Sharing Applications
Geosocial networking applications magnify the concern for location privacy because a user's position can be disclosed to diverse untrusted parties. The Privacy Preserving Obfuscation Environment (Probe) framework supports semantic-location cloaking to ...
Personal information concerns and provision in social network sites: Interplay between secure preservation and true presentation
Encouraging users of social network sites SNS to actively provide personal information is vital if SNS are to prosper, but privacy concerns have hindered users from giving such information. Previous research dealing with privacy concerns has studied ...
Comments