Arturo Servin

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Cloud computing offers the potential to dramatically reduce the cost of software services through the commoditization of information technology assets and on-demand usage patterns. However, the complexity of determining resource provision policies for applications in such complex environments introduces significant inefficiencies and has driven the(More)
Intrusion Detection has been investigated for many years and the field has matured. Nevertheless, there are still important challenges, e.g., how an IDS can detect new and complex distributed attacks. To tackle these problems, we propose a distributed Reinforcement Learning (RL) approach in a hierarchical architecture of network sensor agents. Each network(More)
We describe a practical approach applying the UML 2.0 standard MARTE profile to model stochastic interactive application workflows, using the PapyrusUML editor. We use the PaStep, PaCommStep, PaLogicalResource and GaCommHost MARTE stereotypes and find them sufficient for stochastic modelling with the exception of being unable to define non-standard(More)
This thesis presents a novel approach to provide adaptive mechanisms to detect and categorise Flooding-Base DoS (FBDoS) and Flooding-Base DDoS (FBDDoS) attacks. These attacks are generally based on a flood of packets with the intention of overfilling key resources of the target, and today the attacks have the capability to disrupt networks of almost any(More)
The increasing number of security incidents against computer networks has made insufficient network management and intrusion detection approaches to maintain and to protect these complex systems. Even distributed intrusion detection seems to be not enough if it is used isolated from other disciplines. My research will focus in how network and security(More)
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