基于查询热度的密钥索引缓存

金伟; 李凤华; 周紫妍; 孙喜洋; 郭云川

doi:10.11959/j.issn.2096-109x.2023008

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基于查询热度的密钥索引缓存

学术论文 | 更新时间：2024-06-03

- 基于查询热度的密钥索引缓存
- Cache of cryptographic key based on query popularity
- 网络与信息安全学报 2023年9卷第1期页码：83-91
- 作者机构：
  
  1. 中国科学院信息工程研究所，北京 100093
  2. 中国科学院大学网络空间安全学院，北京 100049
  3. 中国信息通信研究院，北京 100191
- 作者简介：
  
  [ "金伟（1994- ），女，北京人，中国科学院信息工程研究所博士生，主要研究方向为大数据访问控制与密钥管理" ]
  [ "李凤华（1966- ），男，湖北浠水人，博士，中国科学院信息工程研究所研究员、博士生导师，主要研究方向为网络与系统安全、信息保护、隐私计算" ]
  [ "周紫妍（1998- ），女，河北秦皇岛人，中国科学院信息工程研究所博士生，主要研究方向为访问控制" ]
  [ "孙喜洋（1996- ），女，黑龙江齐齐哈尔人，中国科学院信息工程研究所硕士生，主要研究方向为访问控制" ]
  [ "郭云川（1977- ），男，四川营山人，博士，中国科学院信息工程研究所正高级工程师、博士生导师，主要研究方向为访问控制、形式化方法" ]
- 基金信息：
  
  国家自然科学基金;The National Key Research and Development Program of China(U1836203)
- DOI：10.11959/j.issn.2096-109x.2023008
  中图分类号： TP393
- 网络首发：2023-02，
  
  纸质出版：2023-02-25
- 稿件说明：
移动端阅览
金伟, 李凤华, 周紫妍, 等. 基于查询热度的密钥索引缓存[J]. 网络与信息安全学报, 2023,9(1):83-91.

Wei JIN, Fenghua LI, Ziyan ZHOU, et al. Cache of cryptographic key based on query popularity[J]. Chinese Journal of Network and Information Security, 2023, 9(1): 83-91.
金伟, 李凤华, 周紫妍, 等. 基于查询热度的密钥索引缓存[J]. 网络与信息安全学报, 2023,9(1):83-91. DOI： 10.11959/j.issn.2096-109x.2023008.

Wei JIN, Fenghua LI, Ziyan ZHOU, et al. Cache of cryptographic key based on query popularity[J]. Chinese Journal of Network and Information Security, 2023, 9(1): 83-91. DOI： 10.11959/j.issn.2096-109x.2023008.

摘要

在当前的分布式文件系统（HDFS，Hadoop distributed file system）密钥管理系统中，加密区密钥在启动时全部加载至内存，提供密钥服务。随着密钥资源的增加，占据的内存空间也随之增长，带来内存空间不足和密钥索引瓶颈，如何组织缓存数据、高效处理未命中密钥的查询，如何调整缓存中的密钥资源，如何精准预测密钥的使用这三大要点是解决该瓶颈的关键所在。为了实现细粒度高效缓存，提高密钥使用效率，从密钥索引数据结构、密钥置换算法、密钥预取策略分析3个方面出发，设计了密钥缓存置换的模块架构，计算密钥热度，设置密钥置换算法。具体地，在密钥热度计算与缓存置换方面，从密钥所绑定的文件系统和用户出发，分析影响密钥缓存热度的潜在影响要素，构建密钥使用热度的基本模型，采用哈希表与小顶堆链表组合的方式，维护在用密钥的热度，基于热度识别设置淘汰算法，由时间控制器调整密钥使用，动态更新缓存中的密钥，从而实现基于热度计算的密钥差异化置换。在密钥预取策略分析方面，综合考虑业务流程和用户访问存在时间周期维度的规律，通过日志挖掘获取密钥使用规律，分析密钥预置策略。实验表明，所提密钥置换算法可在降低内存占用的同时，有效提升缓存命令率和密钥查询效率，降低密钥文件I/O交互对查询性能的影响。

Abstract

In the current HDFS (Hadoop Distributed File System) key management system

the encryption zone keys are all loaded into the memory during startup of key service.With the increase of the key resource

the occupied memory space also grows

bringing the bottleneck of memory space and key indexing.There are three challenges induced: how to organize cached data and efficiently handle queries with missed keys

how to adjust key resources in the cache

and how to accurately predict the use of keys.In order to achieve fine-grained and efficient caching and improve the efficiency of key use

key caching optimization was considered from three aspects: key index data structure

key replacement algorithm

and key prefetching strategy.An architecture of key cache replacement module was designed

and then a key replacement algorithm based on the query frequency was set.Specifically

from the perspective of heat computing and key replacement

the potential influencing factors affecting the popularity of key cache were analyzed which considered the file system and user of key management system.Besides

the basic model of key usage popularity was constructed.The hash table and minheap linked list was combined to maintain the heat of the key in use

and the elimination algorithm was set based on heat identification.The key in the cache was dynamically updated

and key usage was adjusted by the time controller

so as to realize key replacement according to the key heat.For key prefetching

key usage rules were obtained through log mining and periodical usage analyzing of key provisioning policies

which considered business processes and the time period dimension of user accessing.Experimental results show that the proposed key replacement algorithm can effectively improve the hit rate of cache queries

reduce memory usage

and ameliorate the impact of key file I/O interaction on query performance.

关键词

Keywords

references

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