Pinto: Enabling video privacy for commodity IoT cameras
- Authors
- Yu, Hyunwoo; Lim, Jaemin; Kim, Kiyeon; Lee, Suk bok
- Issue Date
- Oct-2018
- Publisher
- Association for Computing Machinery
- Keywords
- IoT cameras; Video authenticity; Visual privacy
- Citation
- Proceedings of the ACM Conference on Computer and Communications Security, pp.1089 - 1101
- Indexed
- SCIE
SCOPUS
- Journal Title
- Proceedings of the ACM Conference on Computer and Communications Security
- Start Page
- 1089
- End Page
- 1101
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/7901
- DOI
- 10.1145/3243734.3243830
- ISSN
- 1543-7221
- Abstract
- 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. © 2018 Association for Computing Machinery.
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