Name
Abstract | ||
|---|---|---|
This paper proposed a multi-keyword ciphertext search, based on an improved-quality hierarchical clustering (MCS-IQHC) method. MCS-IQHC is a novel technique, which is tailored to work with encrypted data. It has improved search accuracy and can self-adapt when performing multi-keyword ciphertext searches on privacy-protected sensor network cloud platforms. Document vectors are first generated by combining the term frequency-inverse document frequency (TF-IDF) weight factor and the vector space model (VSM). The improved quality hierarchical clustering (IQHC) algorithm then generates document vectors, document indices, and cluster indices, which are encrypted via the k-nearest neighbor algorithm (KNN). MCS-IQHC then returns the top-k search result. A series of experiments proved that the proposed method had better searching efficiency and accuracy in high-privacy sensor cloud network environments, compared to other state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/s18093047 | SENSORS |
Keywords | Field | DocType |
sensor network,cloud,multi-keyword,ciphertext search,KNN,the top-k result,privacy protection | Electronic engineering,Ciphertext,Engineering,Wireless sensor network,Distributed computing,Cloud computing | Journal |
Volume | Issue | Citations |
18 | 9.0 | 0 |
PageRank | References | Authors |
0.34 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lixia Xie | 1 | 12 | 3.66 |
| Ziying Wang | 2 | 0 | 0.34 |
| Yue Wang | 3 | 960 | 143.63 |
| Hongyu Yang | 4 | 19 | 4.73 |
| Jiyong Zhang | 5 | 3 | 0.83 |