Bio-Inspired Formal Model for Space/Time Virtual Machine Randomization and Diversification
Noor O. Ahmed, Bharat Bhargava · IEEE Transactions on Cloud Computing · 2020
Studies on resiliency against system attacks have contributed well established defensive techniques, sound protocols and paradigms in distributed systems’ literature. One of this contribution is credited to redundancy and replication techniques which is proven to be a double–edged–sword, by increasing the number of nodes inherently increases the system's attack-vector – the set of ways an attacker can compromise a system. To remedy this issue, system randomization and diversification has been considered as an effective defensive strategy, referred to as a Moving Target Defense (MTD). In this article, we introduce a bio-inspired formal model for space/time system randomization/diversification and a quantification scheme for virtual machines (VMs) in a cloud computing environment. We show the practicality of the model with a MTD framework(Mayflies)integrated into the cloud management software stack(OpenStack)and illustrate with realistic VM attacks and proactive defense use cases.