In this paper,we study the problem of privacy-preserving top-k keyword similarity search over outsourced cloud data.Taking edit distance as a measure of similarity,we first build up the similarity keyword sets for all...In this paper,we study the problem of privacy-preserving top-k keyword similarity search over outsourced cloud data.Taking edit distance as a measure of similarity,we first build up the similarity keyword sets for all the keywords in the data collection.We then calculate the relevance scores of the elements in the similarity keyword sets by the widely used tf-idf theory.Leveraging both the similarity keyword sets and the relevance scores,we present a new secure and efficient treebased index structure for privacy-preserving top-k keyword similarity search.To prevent potential statistical attacks,we also introduce a two-server model to separate the association between the index structure and the data collection in cloud servers.Thorough analysis is given on the validity of search functionality and formal security proofs are presented for the privacy guarantee of our solution.Experimental results on real-world data sets further demonstrate the availability and efficiency of our solution.展开更多
Objective video quality assessment plays a very important role in multimedia signal processing. Several extensions of the structural similarity （SSIM） index could not predict the quality of the video sequence effect...Objective video quality assessment plays a very important role in multimedia signal processing. Several extensions of the structural similarity （SSIM） index could not predict the quality of the video sequence effectively. In this paper we propose a structural similarity quality metric for videos based on a spatial-temporal visual attention model. This model acquires the motion attended region and the distortion attended region by computing the motion features and the distortion contrast. It mimics the visual attention shifting between the two attended regions and takes the burst of error into account by introducing the non-linear weighting fimctions to give a much higher weighting factor to the extremely damaged frames. The proposed metric based on the model renders the final object quality rating of the whole video sequence and is validated using the 50 Hz video sequences of Video Quality Experts Group Phase I test database.展开更多
基金supported partly by the following funding agencies:the National Natural Science Foundation(No.61170274)the Innovative Research Groups of the National Natural Science Foundation(No.61121061)+1 种基金the National Key Basic Research Program of China (No.2011CB302506)Youth Scientific Research and Innovation Plan of Beijing University of Posts and Telecommunications(No. 2013RC1101)
文摘In this paper,we study the problem of privacy-preserving top-k keyword similarity search over outsourced cloud data.Taking edit distance as a measure of similarity,we first build up the similarity keyword sets for all the keywords in the data collection.We then calculate the relevance scores of the elements in the similarity keyword sets by the widely used tf-idf theory.Leveraging both the similarity keyword sets and the relevance scores,we present a new secure and efficient treebased index structure for privacy-preserving top-k keyword similarity search.To prevent potential statistical attacks,we also introduce a two-server model to separate the association between the index structure and the data collection in cloud servers.Thorough analysis is given on the validity of search functionality and formal security proofs are presented for the privacy guarantee of our solution.Experimental results on real-world data sets further demonstrate the availability and efficiency of our solution.
文摘Objective video quality assessment plays a very important role in multimedia signal processing. Several extensions of the structural similarity （SSIM） index could not predict the quality of the video sequence effectively. In this paper we propose a structural similarity quality metric for videos based on a spatial-temporal visual attention model. This model acquires the motion attended region and the distortion attended region by computing the motion features and the distortion contrast. It mimics the visual attention shifting between the two attended regions and takes the burst of error into account by introducing the non-linear weighting fimctions to give a much higher weighting factor to the extremely damaged frames. The proposed metric based on the model renders the final object quality rating of the whole video sequence and is validated using the 50 Hz video sequences of Video Quality Experts Group Phase I test database.
