الفهرس 
1 IntroductionOnly 14 pages are availabe for public view
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Abstract
Security is one of the major challenges in Cloud Computing. This thesis
presents an Online Smart Disguise Framework (OSDF) for cloud computing
security. The OSDF employs dynamic, proactive, and real-time
Moving-Target Defense (MTD) against cloud computing attacks. The
OSDF relies on two main pillars. The first pillar is a behavior-obscuring
module that frequently live-migrates Virtual Machines (VMs) between
heterogeneously configured computing nodes to avoid co-residency and
virtualization based attacks. The second pillar limits attack dispersion
between same-host VMs by migrating maliciously behaving VMs to remote
isolated compute node acting as a quarantine zone. This pillar is guided by
a smart Intrusion Detection System (IDS) to monitor the VM’s system calls
that searching for suspicious activities. To evaluate the proposed OSDF’s
efficiency and effectiveness on limiting attack dispersion, we devised
Vulnerable Exposed Attacked Recovered (VEAR) mathematical model.
The VEAR model inspired by an epidemiological model commonly used to
investigate disease dispersion on cooperative communities called Susceptible
Exposed Infected Recovered (SEIR) epidemic model. The implementation
of the OSDF is conducted on OpenStack private cloud. The Simulation
results show the effectiveness of OSDF MTD approach in decreasing the
number of attacked VMs even for fast-spreading worms. Furthermore,both
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the NAS Parallel Benchmark (NPB) and the SysBench are used to evaluate
OSDF’s efficiency for cloud-hosted VMs running both statefull and stateless
applications.