An Extended Video Database Model for Supporting Finer-Grained Multi-Policy and Multi-Level Access Controls

The growing amount of multimedia data available to the average user has reached a critical phase, where methods for indexing, searching, and efficient retrieval are needed to manage the information overload. Many research works related to this field have been conducted within the last few decades and consequently, some video database models have been proposed. Most of the modern video database models make use of hierarchical structures to organize huge amount of videos to support video retrieval efficiently. Even now, among open research issues, video database access control is still an interesting research area with many proposed models. In this paper, we present a hybrid video database model which is a combination of the hierarchical video database model and annotations. In particular, we extend the original hierarchical indexing mechanism to add frames and salient objects at the lowest granularity level in the video tree with the aim to support multi-level access control. Also, we give users more solutions to query for videos based on the video contents using annotations. In addition, we also suggest the original database access control model to fit the characteristics of video data. Our modified model supports both multiple access control policies, meaning that a user may be affected by multiple polices, and multi-level access control, meaning that an authorization may be specified at any video level. Theoretical analyses and experimental results with real datasets are presented that confirm the correctness and efficiency of our approach.