What is it about?
We initiate the study of scalable encrypted video search in which a client can search videos similar to an image query. Our modular framework abstracts intrinsic attributes of videos in semantics and visuals to capture their contents. We advocate two-step searches by incorporating lightweight searchable encryption techniques for pre-screening and an interactive approach for fine-grained search. We provide two instantiations – The basic one searches over semantic keywords, feature extraction, and locality-sensitive hash-based visual representations. The advanced one employs forward and backward private searchable encryption [CCS 2017] over deep hashing [CVPR 2020]. Our experimental results illustrate their practical performance over multiple real-world datasets.
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Why is it important?
Our work studies the following gap: Video-based services have become popular. Clients often outsource their videos to the cloud to relieve local maintenance. However, privacy has emerged as a major concern since many videos contain sensitive information. While retrieving (unencrypted) videos has been widely studied, encrypted multimedia retrieval receives rare attention, at best in a limited form of similarity searches on images
Perspectives
We hope our work can build the bridge and stimulate further research in processing encrypted data and video retrieval.
Yu Zheng
Chinese University of Hong Kong
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This page is a summary of: Encrypted video search, June 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3524273.3528190.
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