Predicting Security Events in Cloud Computing

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Singh, Vivek; Dutta, Kaushik
artifact description
Organizations migrate to the cloud computing environment to achieve cost reduction, business agility, and elasticity. However, cloud migration brings another set of challenges such as data security & privacy, resource management, and compliance. Recently, cloud vendors have started offering services to their customers to collect detailed logs of events and resource utilization. However, the cloud computing ecosystem lacks frameworks, models, and IT artifacts to analyze such logs to draw business insights and address the above challenges. Following Design science research paradigm, we present a Gaussian Bayesian Network based approach for learning the underlying dependencies among the events in cloud services to determine the antecedents and consequences of security related events. Moreover, using our model, we predict the security related events with average mean error of 0.13 events for one day ahead forecast. We further discuss our research implications for software development, security, and IT audit in cloud computing environment.