Santiago Fernández-Lorenzo

University of A Coruña | UDC

Computer systems are facing an increased number of security threats, specially regarding Intrusion detection (ID). From the point of view of Machine learning, ID presents many of the new cutting-edge challenges: tackle with massive databases, distributed learning and privacy-preserving classification. In this work, a new approach for ID capable of...

In recent years, Machine Learning (ML) has witnessed a great increase of storage capacity of computer systems and an enormous growth of available information to work with thanks to the WWW. This has raised an opportunity for new real life applications of ML methods and also new cutting-edge ML challenges like: tackle with massive databases, Distrib...

Evolutionary agents are flexible, agile, capable of learning, and appropriate for problems with changing conditions or where the correct solution cannot be known in advance. Evolutionary Multi-Agent systems, therefore, consist of populations of agents that learn through interactions with the environment and with other agents and which are periodica...