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Yang, Y., Lu, K., Cheng, H., Fu, M., Li, Z..  2020.  Time-controlled Regular Language Search over Encrypted Big Data. 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). 9:1041—1045.

The rapid development of cloud computing and the arrival of the big data era make the relationship between users and cloud closer. Cloud computing has powerful data computing and data storage capabilities, which can ubiquitously provide users with resources. However, users do not fully trust the cloud server's storage services, so lots of data is encrypted and uploaded to the cloud. Searchable encryption can protect the confidentiality of data and provide encrypted data retrieval functions. In this paper, we propose a time-controlled searchable encryption scheme with regular language over encrypted big data, which provides flexible search pattern and convenient data sharing. Our solution allows users with data's secret keys to generate trapdoors by themselves. And users without data's secret keys can generate trapdoors with the help of a trusted third party without revealing the data owner's secret key. Our system uses a time-controlled mechanism to collect keywords queried by users and ensures that the querying user's identity is not directly exposed. The obtained keywords are the basis for subsequent big data analysis. We conducted a security analysis of the proposed scheme and proved that the scheme is secure. The simulation experiment and comparison of our scheme show that the system has feasible efficiency.

Ding, W., Wang, J., Lu, K., Zhao, R., Wang, X., Zhu, Y..  2017.  Optimal Cache Management and Routing for Secure Content Delivery in Information-Centric Networks with Network Coding. 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC). :267–274.

Information-Centric Network (ICN) is one of the most promising network architecture to handle the problem of rapid increase of data traffic because it allows in-network cache. ICNs with Linear Network Coding (LNC) can greatly improve the performance of content caching and delivery. In this paper, we propose a Secure Content Caching and Routing (SCCR) framework based on Software Defined Network (SDN) to find the optimal cache management and routing for secure content delivery, which aims to firstly minimize the total cost of cache and bandwidth consumption and then minimize the usage of random chunks to guarantee information theoretical security (ITS). Specifically, we firstly propose the SCCR problem and then introduce the main ideas of the SCCR framework. Next, we formulate the SCCR problem to two Linear Programming (LP) formulations and design the SCCR algorithm based on them to optimally solve the SCCR problem. Finally, extensive simulations are conducted to evaluate the proposed SCCR framework and algorithms.