Enabling Personalized Search over Encrypted Outsourced Data with Efficiency Improvement
By Zhangjie Fu, Kui Ren, Jiangang Shu, Xingming Sun, Fengxiao Huang. IEEE Transactions on Parallel and Distributed Systems, 2016
743 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/3ad87eb6fd1983fbfc73bfbc7d5a11d4018d3f21
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In Artificial Intelligence
In Information Systems
Citations in the corpus
- Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks (2016, background): “AS smart mobile devices have seen advanced technology and design, they facilitate us with a pervasive and powerful platform to realize many novel mobile applications [1][2].”
- An Efficient Public Auditing Protocol With Novel Dynamic Structure for Cloud Data (2017, background): “Cloud storage has been studied in recent years as one of the hot spots in cloud computing [18], [19].”
- Moth search algorithm: a bio-inspired metaheuristic algorithm for global optimization problems (2016, background): “However, modern nature-inspired metaheuristic algorithms have been found to be effective in coming up with optimal or near-optimal solutions for these types of NP-hard problems, such as data encryption [1], and image processing [2].”
- A Privacy-Preserving and Copy-Deterrence Content-Based Image Retrieval Scheme in Cloud Computing (2016, methodology): “Afterwards, plenty of methods have been proposed under different threat models to achieve various search functionalities, such as similarity search [6]–[8], multikeyword ranked search [9]–[12], dynamic search [11], [13]– [15], etc.”
- An efficient public-key searchable encryption scheme secure against inside keyword guessing attacks (2017, background): “How to efficiently search over encrypted data thus becomes an important and interesting problem, and has attracted many researchers’ attention [7, 23, 42, 38, 31, 16, 34, 21, 17, 15, 32, 40].”