Improving security in cloud by formal modeling of IaaS resources

Nowadays, it is a matter of fact that Cloud is a "must" for all complex services requiring great amount of resources. Big-Data Services are a striking example: they actually perform many kind of analysis (like analytics) on very big repositories. Many File Systems and middleware exist for efficient distribution and management of data and they usually use Cloud Resources. Anyway Several problems arose about Security of data: Virtualization is the base of Cloud resources and, even if we consider data storage as virtually separated elements, security issues exist if privilege escalation allows for gaining control on any data on physical hosts. In this paper we show how it is possible to cope Model Driven Engineering techniques to security analysis and monitoring of Cloud infrastructures. For reducing overhead, we provide a formal profile of hosts thermal behaviors. Depending on services input workloads, we detect and forecast malicious actions by comparisons with real thermal data. (C) 2017 Elsevier B.V. All rights reserved.