A game theoretical approach to defend against co resident attacks in cloud computing preventing co-residence using semi-supervised learning +91-9994232214,7806844441, ieeeprojectchennai@gmail.com, www.projectsieee.com, www.ieee-projects-chennai.com IEEE PROJECTS 2016-2017 ----------------------------------- Contact:+91-9994232214,+91-7806844441 Email: ieeeprojectchennai@gmail.com

1. A Game Theoretical Approach to Defend Against Co-Resident Attacks in Cloud
Computing: Preventing Co-Residence Using Semi-Supervised Learning
Abstract:
While cloud computing has facilitated easy and affordable access to IT resources,
it has also introduced a wide range of security risks from almost every layer and
component of cloud systems. In this paper, we focus on one risk at the virtual
machine level and the co-resident attack, where by constructing various types of
side channels, malicious users can obtain sensitive information from other virtual
machines that co-locate on the same physical server. Most previous work has
focused on the elimination of side channels, or more generally speaking, the
possible countermeasures after attackers co-locate with their targets. In contrast,
we provide a different perspective, and propose a defence mechanism that makes
it difficult and expensive for attackers to achieve co-residence in the first place.
Specifically, we first identify the potential differences between the behaviors of
attackers and legal users. Second, we apply clustering analysis and semi-
supervised learning techniques to classify users. Third, we model the problem as a
two-player security game, and give a detailed analysis of the optimum strategies
for both players. Finally, we demonstrate that the attacker's overall cost is
increased dramatically by one-to-two orders of magnitude as a result of our
defence mechanism.