This document provides an at-a-glance view of the main contributions of my Ph.D. work. This work aims at improving security and trustworthiness of cloud computing environments by developing a model for predicting cloud network traffic, an approach for detecting anomalies in cloud network traffic that relies on traffic prediction, as well as a mechanism for aggregating similar alarms from an IDS in the context of the cloud network traffic. All the benefits and drawbacks of the contributions were demonstrated in realistic simulations using data from real network traces. Furthermore, the evaluations were conducted with well-known metrics and the results show that all the proposed mechanisms were able to outperform similar proposals in literature.
A Prediction-based Approach for Anomaly Detection in the Cloud