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

Principal Investigator: Bharat Bhargava

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 paper, 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 is promising to present a unified framework for resilient cloud systems. Keywords-moving target defense; resiliency; adaptability; cloud security


Other PIs: Norm Ahmed at AFRL Jason Kobes at NGC

Students: Miguel Villarreal-Vasquez

Representative Publications

  • IEEE Transactions on Cloud Computing, IEEE Conference on Cloud Computing, ACM CCS conference and workshop

Keywords: adpatability, mitigation of attacks, Moving target defense

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