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Optimal early warning defense of N-version programming service against co-resident attacks in cloud system

机译:N-Version编程服务对云系统共同居民攻击的最佳预警防御

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Due to the virtual machine co-resident architecture, cloud computing systems are vulnerable to co-resident attacks (CRAs) where a malicious attacker may access and corrupt information of a target user through co-locating their virtual machines on the same physical server. To defend against cyber threats such as the CRA, early warning mechanisms have been developed with the aim to detect and block an attack at a nascent stage. In this paper, we study the optimal strategy of allocating early warning resources to defend against CRAs for the voting-based N-version programming (NVP) service running in the cloud. A probabilistic model is proposed to evaluate the failure probability of the NVP service program and further the expected cost of loss for the considered service. Optimization problems of co-determining the optimal numbers of service program versions and early warning agents are further solved to minimize the expected cost of loss. As demonstrated through examples, the resultant optimal strategies can effectively allocate service and defense resources to defend the NVP cloud service against CRAs.
机译:由于虚拟机共同居民架构,云计算系统容易受到共同驻留攻击(CRAS),其中恶意攻击者可以通过在同一物理服务器上共同定位其虚拟机访问目标用户的信息。为了防御CRA等网络威胁,已经开发了早期预警机制,目的是在新生阶段检测和阻止攻击。在本文中,我们研究了分配早期警告资源的最佳策略,以防御CRAS在云中运行的基于投票的N-Version编程(NVP)服务。提出了一种概率模型来评估NVP服务计划的失败概率,并进一步预期的考虑服务损失成本。共同确定服务计划版本和预警代理的优化问题进一步解决,以最小化预期的损失成本。正如通过示例所证明的,所得最佳策略可以有效地分配服务和国防资源,以防御对阵CRA的NVP云服务。

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