TY - GEN
T1 - ProvCam
T2 - 30th International Conference on Mobile Computing and Networking, ACM MobiCom 2024
AU - Liu, Yuxin
AU - Yao, Zhihao
AU - Chen, Mingyi
AU - Sani, Ardalan Amiri
AU - Agarwal, Sharad
AU - Tsudik, Gene
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s).
PY - 2024/5/29
Y1 - 2024/5/29
N2 - Our perception of reality is under constant threat from ever-improving video manipulation techniques, including deepfakes and generative AI. Therefore, proving authenticity of videos is increasingly important, especially in legal and news contexts. However, it is very challenging to prove it based on post-factum video content analysis. In this work, we take a preventative stance and construct ProvCam, a novel camera module that generates a cryptographic proof of video authenticity. Our solution greatly reduces the size of Trusted Computing Base (TCB) to include the module itself. Moreover, it mitigates tampering during the numerous processing steps between video capture by the camera sensor and generation of the digital video output. To confirm its practicality, we present a complete prototype of ProvCam on a Xilinx FPGA evaluation board. As experiments show, ProvCam incurs a negligible performance overhead (latency and throughput) and small energy consumption overhead when recording a video. It imposes a moderate hardware cost but is relatively small compared to other major components such as SoC. Moreover, it does not change the existing camera software stack and thus can be easily integrated with various camera-bearing devices, such as smartphones.
AB - Our perception of reality is under constant threat from ever-improving video manipulation techniques, including deepfakes and generative AI. Therefore, proving authenticity of videos is increasingly important, especially in legal and news contexts. However, it is very challenging to prove it based on post-factum video content analysis. In this work, we take a preventative stance and construct ProvCam, a novel camera module that generates a cryptographic proof of video authenticity. Our solution greatly reduces the size of Trusted Computing Base (TCB) to include the module itself. Moreover, it mitigates tampering during the numerous processing steps between video capture by the camera sensor and generation of the digital video output. To confirm its practicality, we present a complete prototype of ProvCam on a Xilinx FPGA evaluation board. As experiments show, ProvCam incurs a negligible performance overhead (latency and throughput) and small energy consumption overhead when recording a video. It imposes a moderate hardware cost but is relatively small compared to other major components such as SoC. Moreover, it does not change the existing camera software stack and thus can be easily integrated with various camera-bearing devices, such as smartphones.
KW - Deepfakes
KW - Secure camera
KW - Video provenance
UR - http://www.scopus.com/inward/record.url?scp=85206358891&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85206358891&partnerID=8YFLogxK
U2 - 10.1145/3636534.3649383
DO - 10.1145/3636534.3649383
M3 - Conference contribution
AN - SCOPUS:85206358891
T3 - ACM MobiCom 2024 - Proceedings of the 30th International Conference on Mobile Computing and Networking
SP - 588
EP - 602
BT - ACM MobiCom 2024 - Proceedings of the 30th International Conference on Mobile Computing and Networking
PB - Association for Computing Machinery, Inc
Y2 - 18 November 2024 through 22 November 2024
ER -