2017 Symposium Posters

Posters > 2017

An MTD-based Self-Adaptive Resilience Approach for Cloud Systems


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Primary Investigator:
Bharat Bhargava

Project Members
Miguel Villarreal-Vasquez, Pelin Angin, Norman Ahmed and Bharat Bhargava
Abstract
Advances in cloud computing have made it a feasible and cost-effective solution to improve the resiliency of enterprise systems. However, the replication approach taken by cloud computing to provide resiliency leads to an increase in the number of ways an attacker can exploit or penetrate the systems. This calls for designing cloud systems that can accurately detect anomalies and dynamically adapt themselves to keep performing mission-critical functions even under attacks and failures. In this work, we propose a self-adaptive resiliency approach for cloud enterprise systems that employs a live monitoring and moving target defense based approach to automatically detect deviations from normal behavior and reconfigure critical cloud processes through software-defined networking to mitigate attacks and reduce system downtime. The proposed solution presents a unified framework for resilient cloud systems.