An Intelligent Fuzzy Phrase Search Scheme Over Encrypted Network Data for IoT
Xinrui Ge, Wei Guofu, Jia Yu, Amit Kumar Singh, Naixue Xiong
Abstract
With the popularization of various applications of the Internet of Things (IoT), a large number of smart devices are connected to the IoT to form an interconnected network. Because the amount of network data generated by IoT devices is huge, data owners prefer to outsource these data to the cloud for releasing them from the local storage burden. Meanwhile, in order to protect the privacy of the network data generated by IoT devices, data owners usually encrypt them before outsourcing them to the cloud. Phrase search encryption plays an important role in the IoT-based applications. To the best of our knowledge, all existing phrase search encryption schemes cannot work when user makes spelling errors. In addition, many existing phrase search encryption schemes build the secure index based on the relative position of keywords, which may lead to inaccurate search results. In order to address these problems, we propose an intelligent fuzzy phrase search scheme over encrypted network data for IoT. In this scheme, we construct a fuzzy keyword set for each distinct keyword, which can efficiently address the spelling mistakes. Moreover, we build the binary matrix for the document collection, which can quickly achieve multi-keyword search. In order to accurately determine whether the keywords in the query phrases are consecutive, we build the look-up table for each document. Experimental result shows that the proposed scheme achieves high efficiency and accuracy.