A Secure VM Placement Strategy to Defend against Co-residence Attack in Cloud Datacentres

Q1 Mathematics
Ankita Srivastava, Narander Kumar
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Abstract

With the increasing number of co-residence attacks, the security of the multi-tenant public IaaS cloud environment has become a growing concern. The co-residence attacker creates a side channel to retrieve the secured data. These attacks help the adversary to leak out the sensitive information of the user with whom it is co-located. This paper discusses a secured VM placement technique, Previous Server and Co-resident users First (PSCF), which focuses on facilitating security against the co-residence attack by minimizing the probability of co-locating the malicious user with the authentic user. Co-location resistance and core utilization metrics are utilized to evaluate the algorithm’s performance. The proposed method is simulated, and the result is analysed and compared with existing approaches like Best Fit, Worst Fit, PSSF, and SC-PSSF. It is observed that the proposed approach furnished maximum co-location resistance of 74.32% and a core utilization of 82.63%. Further, the algorithm has shown significant performance in balancing the load and energy consumption. The result has reduced the probability that malicious users co-located with the authentic one, thus reducing the security breach of confidential information.
防御云数据中心共驻攻击的安全虚拟机放置策略
随着同驻攻击的日益增多,多租户公共 IaaS 云环境的安全性日益受到关注。同驻攻击者会创建一个侧信道来检索安全数据。这些攻击会帮助攻击者泄露与其同驻的用户的敏感信息。本文讨论了一种安全的虚拟机放置技术--"上一个服务器和共驻用户优先(PSCF)",该技术的重点是通过最大限度地降低恶意用户与真实用户共驻的概率来提高抵御共驻攻击的安全性。抗同址攻击和核心利用率指标被用来评估算法的性能。对所提出的方法进行了模拟,并将结果与现有方法(如最佳拟合、最差拟合、PSSF 和 SC-PSSF)进行了分析和比较。结果表明,所提出的方法可实现 74.32% 的最大共定位阻力和 82.63% 的内核利用率。此外,该算法在平衡负载和能耗方面表现出了显著的性能。该结果降低了恶意用户与真实用户共同定位的概率,从而减少了机密信息的安全漏洞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.10
自引率
0.00%
发文量
33
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