Moving-Target Defense in Depth: Pervasive Self- and Situation-Aware VM Mobilization across Federated Clouds in Presence of Active Attacks

【Author】 Magdy, Yousra; Azab, Mohamed; Hamada, Amal; Rizk, Mohamed R. M.; Sadek, Nayera

【Source】SENSORS

【影响因子】3.847

【Abstract】Federated clouds are interconnected cooperative cloud infrastructures offering vast hosting capabilities, smooth workload migration and enhanced reliability. However, recent devastating attacks on such clouds have shown that such features come with serious security challenges. The oblivious heterogeneous construction, management, and policies employed in federated clouds open the door for attackers to induce conflicts to facilitate pervasive coordinated attacks. In this paper, we present a novel proactive defense that aims to increase attacker uncertainty and complicate target tracking, a critical step for successful coordinated attacks. The presented systemic approach acts as a VM management platform with an intrinsic multidimensional hierarchical attack representation model (HARM) guiding a dynamic, self and situation-aware VM live-migration for moving-target defense (MtD). The proposed system managed to achieve the proposed goals in a resource-, energy-, and cost-efficient manner.

【Keywords】cloud federation; virtual machines; blockchain; HARM model; moving-target defense; virtualization; cloud migration

【发表时间】2022 DEC

【收录时间】2023-01-04

【文献类型】理论模型

【主题类别】

区块链技术-协同技术-联邦学习