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清华大学学报(自然科学版)  2018, Vol. 58 Issue (4): 395-401,410    DOI: 10.16511/j.cnki.qhdxxb.2018.25.018
  计算机科学与技术 本期目录 | 过刊浏览 | 高级检索 |
基于虚拟机IO序列与Markov模型的异常行为检测
陈兴蜀1, 陈佳昕2, 赵丹丹2, 金鑫2
1. 四川大学 网络空间安全研究院, 成都 610065;
2. 四川大学 计算机学院, 成都 610065
Anomaly detection based on IO sequences in a virtual machine with the Markov mode
CHEN Xingshu1, CHEN Jiaxin2, ZHAO Dandan2, JIN Xin2
1. Cybersecurity Research Institute, Sichuan University, Chengdu 610065, China;
2. School of Computing, Sichuan University, Chengdu 610065, China
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摘要 为检测虚拟机内部的IO异常行为,及时发现已知和未知的虚拟机逃逸攻击,基于硬件辅助虚拟化技术,该文提出了一种基于虚拟机IO序列的异常检测方法,包括:提出了一种异步采集技术高效采集虚拟机IO序列;建立了虚拟机IO序列与虚拟机内部进程的映射关联关系,以细粒度描述虚拟机自身IO行为;提出了一种基于双层Hash表的虚拟机IO短序列生成算法,并采用Markov链模型检测异常虚拟机IO序列。在KVM(Kernel-based virtual machine)虚拟化环境下设计并实现原型系统VMDec(virtual machine detecting),通过实验评测了VMDec系统的功能和性能。实验结果表明:VMDec能有效检测出虚拟机内部基于IO的恶意攻击以及已知和未知的虚拟机逃逸攻击,且检测误报率和性能开销在可接受范围内。
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陈兴蜀
陈佳昕
赵丹丹
金鑫
关键词 IO序列异常检测虚拟机逃逸Markov链短序列    
Abstract:A abnormal IO behavior in virtual machines is monitored to discover known and unknown virtual machine escape attacks. Hardware-assisted virtualization is used here in an anomaly detection method for IO sequences in virtual machines including asynchronous acquisition to efficiently collect the IO sequences of the virtual machine, relating the IO sequences with the processes running in the virtual machine for a fine-grained description of the virtual machine's IO behavior, and an algorithm for generating short IO sequences in virtual machines based on a double-layer hash table and a Markov chain model to detect the IO sequences of malicious virtual machines. A virtual machine detection system was implemented on a Kernel-based virtual machine (KVM) to evaluate the effectiveness of this system. The results show that the system can effectively detect some IO based on security threats and some known and unknown virtual machine escape attacks with an acceptable false alarm rate and performance overhead.
Key wordsIO sequence    anomaly detection    virtual machine (VM) escape    Markov chain    short sequence
收稿日期: 2017-08-18      出版日期: 2018-04-15
ZTFLH:  TP309  
基金资助:国家自然科学基金资助项目(61272447)
作者简介: 陈兴蜀(1968-),女,教授。E-mail:chenxsh@scu.edu.cn
引用本文:   
陈兴蜀, 陈佳昕, 赵丹丹, 金鑫. 基于虚拟机IO序列与Markov模型的异常行为检测[J]. 清华大学学报(自然科学版), 2018, 58(4): 395-401,410.
CHEN Xingshu, CHEN Jiaxin, ZHAO Dandan, JIN Xin. Anomaly detection based on IO sequences in a virtual machine with the Markov mode. Journal of Tsinghua University(Science and Technology), 2018, 58(4): 395-401,410.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2018.25.018  或          http://jst.tsinghuajournals.com/CN/Y2018/V58/I4/395
  图1 VMDec总体架构图
  图2 异步采集过程图
  图3 task_struct与thread_info关系图
  图4 虚拟机进程语义动态获取示意图
  图5 双层 Hash表示意图
  图6 虚拟机IO 短序列生成算法
  表1 功能测试结果
  表1 功能测试结果
  表2 性能测试结果
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