How to improve the Systems Security using Data Mining

During this week, Geneura Team has welcomed Professor Ja’far Alqatawna from the University of Jordan. Ja’far Alqatawna is an Associate Professor at King Abdullah II School for Information Technology, University of Jordan. He received his B.Eng degree in Computer Engineering from Mu’tah University, Jordan, followed by MSc. in Information and Communication Systems Security from The Royal Institute of Technology (KTH), Sweden. In 2010 He has been awarded his Ph.D. Degree in Computer Information Systems with specialisation in Information Security and e-Business from Sheffield Hallam University, UK. He was part of researching projects for investigating XACML as a policy language for distributed networks at Security, Policy and Trust Lab (SPOT) of the Swedish Institute of Computer Science (SICS), Sweden. His current research interests are in the field of Cybersecurity in which he tries to look for multi-dimensional approaches that go beyond the technical dimension in order to develop trustworthy Cyberspace. Yesterday he presented a talk about the use of Data Mining for improving the security of the software systems which you can see in slide share, For this time, he presented and discussed several security areas in which data mining has the possibility of enhancing the existing security methods.


Jornada sobre Smart Cities y Movilidad

El jueves 26 de noviembre de 2015 celebramos en la Sala de Usos Múltiples del CITIC-UGR (C/ Periodista Rafael Gómez, nº 2) la Jornada sobre Smart Cities y Movilidad, enmarcada en el Programa De Ayudas Genil Para Realización De Actividades Por Grupos De Investigación Interdiciplinares (RAGII-2015).

El objeto de esta Jornada fue la investigación en el área de la gestión de la movilidad, internet de las cosas y smart cities.

A lo largo de la mañana asistimos a varias conferencias, impartidas por responsables del Area de Movilidad del Ayuntamiento de Granada, de varias empresas, así como por parte de investigadores de la Universidad de Granada en este ámbito.

Los objetivos finales fueron crear sinergia entre los diversos grupos de investigación y empresas de este área, así como facilitar el contacto de cara a promover colaboraciones, tales como solicitar proyectos, o realizar transferencia de conocimiento a partir de los resultados de investigación.

El desarrollo de la Jornada se basó en presentaciones de unos 40 minutos, en las que el ponente, por parte del Área de Movilidad del Ayuntamiento de Granada, Nazaríes, UXMobile, Geokeda, e investigadores de los grupos de investigación, comentaron los proyectos en los que trabajan actualmente en el área de las smart cities, así como las problemáticas, y los retos a los que se enfrentan.


GeNeura at European Project MUSES Final Review

GeNeura’s members have been working in the three-year long, FP7 European project MUSES, which faced its last review last week at the European Commision Beaulieu Quarter Buildings in Brussels.

UGR was one of the partners participating in this project. More concretely, GeNeura’s members have contributed by leading WP2 – MUSES framework definition and integration during the completion of tasks to define the MUSES System Architecture. In addition, GeNeura’s research has been applied to the project in WP5 – Self-adaptive event correlation, lead by a Spanish security company S2 Grupo. The main purpose of this WP was to develop a system which, on the one side, uses event correlation to detect Security Policy violations and, on the other side, performs an analysis of all the data in the system and creates new Security Policies or enhances the existing ones. Different types of classification, rule association, and clustering algorithms, as well as Data Mining techniques, have been applied with satisfactory results. These results were specially welcomed by the comission, ponting that such a system will be very helpful to enhance security. Also, MUSES is an Open Software project, and you can contribute at

The results were presented by S2 Grupo and GeNeura together. The slides are now published on Slideshare:

It has been a pleasure for GeNeura to work in MUSES


[Paper] Going a Step Beyond the Black and White Lists for URL Accesses in the Enterprise by means of Categorical Classifiers

Our work titled Going a Step Beyond the Black and White Lists for URL Accesses in the Enterprise by means of Categorical Classifiers, as part of the researh under the MUSES project, has been presented today at the ECTA 2014 conference.


Corporate systems can be secured using an enormous quantity of methods, and the implementation of Black or White lists is among them.
With these lists it is possible to restrict (or to allow) the users the execution of applications or the access to certain URLs, among others. This paper is focused on the latter option. It describes the whole processing of a set of data composed by URL sessions performed by the employees of a company; from the preprocessing stage, including labelling and data balancing processes, to the application of several classification algorithms. The aim is to define a method for automatically make a decision of allowing or denying future URL requests, considering a set of corporate security policies.
Thus, this work goes a step beyond the usual black and white lists, since they can only control those URLs that are specifically included in them, but not by making decisions based in similarity (through classification techniques), or even in other variables of the session, as it is proposed here.
The results show a set of classification methods which get very good classification percentages (95-97%), and which infer some useful rules based in additional features (rather that just the URL string) related to the user’s access. This led us to consider that this kind of tool would be very useful tool for an enterprise.

You can check the presentation at: .

Out of CPU cycles and in need to do science? No problem!

After the bad experience of spending money in clusters and grids and then spending more time doing maintenance, hack-proofing and installing stuff than science, maybe it is the time to rethink how massive distributed evolutionary computation should be done. Nowadays there are lots of free or use-based resources that can be tapped for doing volunteer-based evolutionary algorithms. That is way my last keynote and tutorial have dealt with that: the IDC Keynote, Low or No Cost Evolutionary computation, which you can access here in Heroku, puts the money where its mouth is: talking and doing volunteer-based evolutionary computing at the same time. The PPSN tutorial, Low or no cost distributed evolutionary computation, touched on the same topic, only longer and with more enphasis on tools.
So finally it is just a matter of a little Javascript and using free cloud resources and you can have your very own massive distributed experiment. Whose results will be published soon enough.

Free access to paper accepted at GECCO’14

During 1 month, papers accepted at GECCO1’4 will be freely available. Thus, you can get and read our papers:

  • “Assessing different architectures for evolutionary algorithms in javascript” by Juan Julián Merelo, Pedro Castillo, Antonio Mora, Anna I. Esparcia-Alcázar, Víctor M. Rivas Santos (doi 10.1145/2598394.2598460) at
  • NodEO, a multi-paradigm distributed evolutionary algorithm platform in JavaScript” by Juan-Julián Merelo, Pedro Castillo, Antonio Mora, Anna Esparcia-Alcázar, Víctor Rivas-Santos (doi:10.1145/2598394.2605688) at
  • “Enforcing corporate security policies via computational intelligence techniques” by Antonio M. Mora, Paloma De las Cuevas, Juan Julián Merelo, Sergio Zamarripa, Anna I. Esparcia-Alcázar (doi: 10.1145/2598394.2605438) at
  • A methodology for designing emergent literary backstories on non-player characters using genetic algorithms”, by Rubén Héctor García-Ortega, Pablo García-Sánchez, Antonio Miguel Mora, Juan Julián Merelo (doi: 10.1145/2598394.2598482) at


Workshop on Spatially Structured Metaheuristics

We cordially invite you to attend the following two-presentations on Spatially Structured Metaheuristics. This mini-workshop will be held at 11.30 a.m. in the CITIC-UGR building (June 26th, 2014).

Spatially Structured Metaheuristics: Principles and Practical Applications
by Juan Luis Jiménez Laredo (University of Luxembourg)

A relevant number of metaheuristics are based on population. Although conventions may establish different names, individuals in evolutionary algorithms, ants in ant colony optimization or particles in particle swarm optimization belong to the same side of a coin: they are all  atomic elements of the population (a.k.a. building-blocks). In this context, spatially structured metaheuristics investigate how to improve the performance of metaheuristics by confining these elements in neighborhoods. This talk aims at presenting the working principles of spatially structured metaheuristics and practical applications to enhance diversity, scalability and robustness.


Spatially Structured Metaheuristics: Dynamic and Self-organized Topologies
by Carlos M. Fernandes (University of Lisbon)

Population based metaheuristics are computational search or optimization methods that use a population of possible solutions to a problem. These solutions are able communicate, interact and/or evolve. Two types of strategies for structuring population are possible. In panmictic populations, every individual is allowed to interact with every other individual. In non-panmictic metaheuristics, also called spatially structured population-based metaheuristics, the interaction is restricted to a pre-defined or evolving structure (network). Traditional spatially structured metaheuristics are built on pre-defined static networks of acquaintances over which individuals can interact. However, alternative strategies that overcome some of the difficulties and limitations of static networks (extra design and tuning effort, ad hoc decision policies, rigid connectivity, and lack of feedback from the problem structure and search process) are possible. This talk discusses dynamic topologies for spatially structured metaheuristics and describes a new model for structuring populations into partially connected and self-organized networks. Recent applications of the model on Evolutionary Algorithms and Particle Swarm Optimization are given and discussed.