Multi-keyword Ranked Ciphertext Retrieval Scheme Based on Clustering Index
-
摘要: 为了提高密文检索的效率和精度，提出基于聚类索引的多关键字排序密文检索方案.首先利用改进的Chameleon算法对文件向量聚类，聚类过程中通过记录关键字位置对文件向量进行降维处理.其次，提出适合聚类索引的检索算法，使得在查询过程中可以排除大量与查询向量无关的文件向量，减少了不必要的计算消耗.再次，在聚类过程中引入杰卡德相似系数来计算文件向量之间的相似度以及设定合适的阈值提高聚类质量.在真实数据集上进行了实验，理论分析和实验结果表明：在保障数据隐私安全的前提下，该方案较传统的密文检索方案有效地提高了密文检索的效率与精度.
-
关键词:
- 云安全 /
- 密文检索 /
- 排序检索 /
- 聚类索引 /
- Chameleon算法
Abstract: Data owners prefer to outsource documents in an encrypted form for the purpose of privacy preserving. But existed encrypting technologies make it difficult to search for encrypted data, which limit the availability of outsourced data. This will make it even more challenging to design ciphertext search schemes that can provide efficient and reliable online information retrieval. In order to improve the efficiency and precision of ciphertext retrieval, we propose a multi-keyword ciphertext retrieval scheme based on clustering index. Firstly, the improved Chameleon algorithm is used to cluster the file vectors during which the file vectors are dimensioned by recording the position of the key words. Secondly, a retrieval algorithm suitable for clustering index is proposed, which makes it possible to eliminate a large number of file vectors irrelevant to the query vector in the query process, and reduce unnecessary consumption. Finally, in the clustering process, Jaccard similarity coefficient is introduced to calculate the similarity between the file vectors and to set the appropriate threshold to improve the quality of the cluster. The theory analysis and experimental results show that the scheme can effectively improve the efficiency and precision of ciphertext retrieval under the premise of guaranteeing the privacy and security of data.-
Keywords:
- cloud security /
- ciphertext search /
- ranked search /
- clustering index /
- Chameleon algorithm
-
-
期刊类型引用(8)
1. 郝志刚，秦丽. 基于多属性综合评价的食品安全标准引用网络重要节点发现方法. 计算机应用. 2022(04): 1178-1185 . 
百度学术
2. 贾慧娟，刘园，史爱静，张霄宏. 一种基于标签传播的重叠社区发现算法. 小型微型计算机系统. 2022(04): 773-778 . 百度学术
3. 刘海姣，马慧芳，赵琪琪，李志欣. 融合用户兴趣偏好与影响力的目标社区发现. 计算机研究与发展. 2021(01): 70-82 . 本站查看
4. 张中军，于来行，李润川. 基于链路结构和转发行为的微博社交网络重叠社区划分方法. 郑州大学学报(理学版). 2021(04): 69-76 . 百度学术
5. 丁建立，邵酉辰. 基于成对约束的多标签传播重叠社区发现方法. 计算机工程与设计. 2020(03): 689-694 . 百度学术
6. 赵霞，张泽华，张晨威，李娴. RGNE:粗糙粒化的网络嵌入式重叠社区发现方法. 计算机研究与发展. 2020(06): 1302-1311 . 本站查看
7. 曾绍华，唐文密，詹林庆，黄秀芬. 基于自适应密度峰值聚类的野外紫色土彩色图像分割. 农业工程学报. 2019(19): 200-208 . 百度学术
8. 林胜青. 基于内容流行度的网络内部缓存智能分布方法. 咸阳师范学院学报. 2019(06): 37-41 . 百度学术
其他类型引用(20)
计量
- 文章访问数: 1201
- HTML全文浏览量: 3
- PDF下载量: 329
- 被引次数: 28
下载:
