计算机科学 ›› 2010, Vol. 37 ›› Issue (1): 42-46.

• 计算机网络与信息安全 • 上一篇    下一篇

一种基于人工免疫技术的存储异常检测系统

黄建忠,裴灿浩,谢长生,陈云亮,方允福   

  1. (华中科技大学-武汉光电国家实验室-光电信息存储研究部暨华中科技大学-数据存储教育部重点实验室 武汉430074)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家“973"重大基础研究项目(2004CB318203)和国家自然科学基金(60603074/60603075)资助。

Research on an Artificial Immune System-based Storage Anomaly Detection

HUANG Jian-thong,PEI Can-hao,XIE Chang-sheng,CHEN Yun-Bang,FANG Yun-f u   

  • Online:2018-12-01 Published:2018-12-01

摘要: 绝大部分认证子系统无法保证账户的真实性,它会将冒用盔窃账户的入侵者视为‘合法’用户。为了过滤这类非法用户,存储安全子系统必须进行访问行为诊断。为了增强存储预警能力,提出一种基于人工免疫的异常检测方案来监控用户的访问行为。若一个访问请求违反了访问控制规则,它就被视为‘异己’,从而给存储安全子系统提供一些警告提示。本方案(Storage Anomaly Detection System, SADS)针对存储层的入侵检测,并关注读/写数据请求,同时与网络入侵检测系统协同构筑了两层检测体系。仿真结果显示,SADS能达到相当高的检测率和较低的误警率,验证了方案可行性。而开销测试表明,SADS子模块的时间开销是可接受的(如对3 MB的数据,其开销控制在11. 6%以内)。

关键词: 存储安全性,异常检测,人工免疫系统,用户访问行为

Abstract: Most authentication sub-systems can not guarantee the authenticity of the account, and an intruder using a stolen account may be regarded as a legitimate user. In order to filter out such illegal users, the storage system should be able to watch for the user access activities. In order to enhance the storage security, the paper proposed an immune anomaly detection scheme to identify the anomalous access behavior. When an access rectuest violates the access control rule,it is viewed as Non-self,so as to provide some storage early warning tips to the storage security subsystem. The proposed storage anomaly detection system (SADS) targets the anomaly detection at storage level and focuses on the read/write data requests, constructing two-layer detection together with the network intrusion detection system (KIDS). The simulation results show the proposed scheme can reach rather high detection rate and low false alarm rate,validating its feasibility. The overhead test exhibits that the computation time caused by SADS is acceptable, e. g below 11. 6% as to 3MB data.

Key words: Storage security, Anomaly detection, AIS, User access behavior

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!