Reliability versus Vulnerability of N-Version Programming Cloud Service Component With Dynamic Decision Time Under Co-Resident Attacks

被引:4
作者
Levitin, Gregory [1 ,2 ]
Xing, Liudong [3 ]
Xiang, Yanping [1 ,2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Comp Sci, Collaborat Auton Comp Lab, Chengdu 611731, Peoples R China
[2] Israel Elect Corp Ltd, POB 10, IL-31000 Haifa, Israel
[3] Univ Massachusetts, Elect & Comp Engn Dept, Dartmouth, MA 02747 USA
关键词
Co-residence attack; dynamic decision time; N-version programming; threshold voting; reliability; vulnerability; virtual machine; VIRTUAL MACHINE ALLOCATION; SIDE-CHANNEL ATTACKS; COMPUTING SYSTEM; VS; SECURITY; PLACEMENT; STRATEGY; PROTECTION;
D O I
10.1109/TSC.2020.3019420
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The virtual machine (VM) co-resident architecture of cloud computing enables simultaneous provision of multiple services to different users, but also makes these services vulnerable to co-resident attacks. For example, by establishing side channels, a malicious attacker can access and even corrupt services performed by other VMs co-residing on the same server as the attacker's VM (AVM). We model a threshold-voting-based N-version programming service component with multiple independent versions simultaneously performing the same requested service to enhance the service reliability. However, the reliability enhancement can be greatly hindered by the co-resident attack, which may corrupt an adequate number of versions leading to a wrong output. We formulate and solve constrained optimization problems that determine the number of service component versions and the voting threshold to balance two conflicting service performance metrics: reliability (service component success probability) and vulnerability (service corruption attack success probability). Two cases respectively having certain and uncertain knowledge about the attacker's power in terms of the number of AVMs are considered. We also investigate impacts of different model parameters on the service performance as well as on solutions to the considered optimization problems through examples.
引用
收藏
页码:1774 / 1784
页数:11
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