Antonio Mora

• PhD Computer Sciences
• Professor (Associate) at University of Granada

Due to the escalating network throughput and security risks, the exploration of intrusion detection systems (IDSs) has garnered significant attention within the computer science field. The majority of modern IDSs are constructed using deep learning techniques. Nevertheless, these IDSs still have shortcomings where most datasets used for IDS lies in...

Intrusion Detection Systems (IDSs) are a primary research area in Cybersecurity nowadays. These are programs or methods designed to monitor and analyze network traffic aiming to identify suspicious patterns/attacks. MSNM (Multivariate Statistical Network Monitoring) is a state-of-the-art algorithm capable of detecting various security threats in re...

An intrusion detection system (IDS) plays a critical role in maintaining network security by continuously monitoring network traffic and host systems to detect any potential security breaches or suspicious activities. With the recent surge in cyberattacks, there is a growing need for automated and intelligent IDSs. Many of these systems are designe...

The IDS serves as a security system that maintains constant surveillance over network traffic and host systems in order to identify any security breaches or potentially concerning activities. Recently. the rise in cyber-attacks has driven the necessity for the development of automated and intelligent network intrusion detection systems. These syste...

Debido al gran aumento en el número de ciberataques, los sistemas de detección de intrusos en red (Network Intrusion Detection Systems, NIDSs) han sido y son frecuentemente utilizados hoy en día. Estos pueden basarse en diversas técnicas, incluyendo aprendizaje automático (Machine Learning), así como aprendizaje profundo (Deep Learning). A su vez,...

Las redes 5G dependen en gran medida de la gestión y el procesamiento basados en software. Las redes definidas por software (SDN) y la virtualización de funciones de red (NFV) forman parte del núcleo de estas. Los servicios ofrecidos dentro de este entorno se componen de varias funciones de red virtuales (VNF) que deben ejecutarse en un orden (norm...

Intrusion Detection Systems (IDSs) are a primary research area in Cybersecurity nowadays. These are programs or methods designed to monitor and analyze network traffic aiming to identify suspicious patterns/attacks. MSNM (Multivariate Statistical Network Monitoring) is a state-of-the-art algorithm capable of detecting various security threats in re...

Messaging platforms are applications, generally mediated by an app, desktop program or the web, mainly used for synchronous communication among users. As such, they have been widely adopted officially by higher education establishments, after little or no study of their impact and perception by the teachers. We think that the introduction of these...

Online reviews are important information that customers seek when deciding to buy products or services. Also, organizations benefit from these reviews as essential feedback for their products or services. Such information required reliability, especially during the Covid-19 pandemic which showed a massive increase in online reviews due to quarantin...

The number of connected devices to Internet is growing every year, making almost everything in touch. However, this scenario increase the probability of systems and communications of suffering security attacks since the attack surface increases proportionally. To counteract against security attacks and threats Network Intrusion Detection Systems (N...

Volume with the Late-Breaking Abstracts submitted to the Evo* 2022 Conference, held in Madrid (Spain), from 20 to 22 of April. These papers present ongoing research and preliminary results investigating on the application of different approaches of Bioinspired Methods (mainly Evolutionary Computation) to different problems, most of them real world...

The use of new technologies such as messaging applications and chatbots in higher education is rapidly growing in Western countries. This entails a careful consideration of the potential opportunities and/or challenges of adopting these tools. Hence, a comprehensive examination of the teachers’ opinions and needs in this discipline can shed light o...

Digital Collectible Cards Games such as Hearthstone have become a very prolific test-bed for Artificial Intelligence algorithms. The main researches have focused on the implementation of autonomous agents (bots) able to effectively play the game. However, this environment is also very attractive for the use of Data Mining (DM) and Machine Learning...

During the recent COVID-19 pandemic, people were forced to stay at home to protect their own and others’ lives. As a result, remote technology is being considered more in all aspects of life. One important example of this is online reviews, where the number of reviews increased promptly in the last two years according to Statista and Rize reports....

Real-Time Strategy (RTS) games are well-known for their substantially large combinatorial decision and state spaces, responsible for creating significant challenges for search and machine learning techniques. Exploiting domain knowledge to assist in navigating the expansive decision and state spaces could facilitate the emergence of competitive RTS...

Introducing new technologies such as messaging platforms, and the chatbots attached to them, in higher education, is rapidly growing. This introduction entails a careful consideration of the potential opportunities and/or challenges of adopting these tools. Hence, a thorough examination of the teachers' experiences in this discipline can shed light...

Intrusion Detection Systems (IDS) are one of the major research application problems in the computer security domain. With the increasing number of advanced network attacks, the improvement of the traditional IDS techniques become a challenge. Efficient ways and methods of identifying, protecting, and analyzing data are needed. In this paper, a com...

5G Networks are strongly dependent on software-based management and processing. Services offered inside this environment are composed of several Virtual Network Functions (VNFs) that must be executed in a (normally) strict order. This is known as Service Function Chaining (SFC) and, given that those VNFs could be placed in different nodes along the...

This paper tries to find the best condition to use chatbots (conversational agents) in higher-education studies after pilots carried out at the University of Granada (Spain). Our aim, along with the rest of partners in EDUBOTS -an Erasmus + European Project which counts with two pedagogical chatbots-, is to improve students’ engagement in class, as...

One of the most crucial problems in the field of business is financial forecasting. Many companies are interested in forecasting their incoming financial status in order to adapt to the current financial and business environment to avoid bankruptcy. In this work, due to the effectiveness of Deep Learning methods with respect to classification tasks...

Volume with the Late-Breaking Abstracts submitted to the Evo* 2021 Conference, held online from 7 to 9 of April 2021. These papers present ongoing research and preliminary results investigating on the application of different approaches of Bioinspired Methods (mainly Evolutionary Computation) to different problems, most of them real world ones.

Evolution is a powerful problem-solving technique, extensively used for designing racing car controllers, but with a series of challenges: an evaluation function that can separate the best controllers from the rest, and a series of operators that can explore different possibilities in the controller search space. Within the context of the TORCS rac...

In the last few years, the Hearthstone AI international Competition has been gaining fame among the scientific community. Several different entries have been presented using varied approaches. One of the best, EVA, was based on a Greedy approach combined with an Evolutionary Algorithm. However, almost all the proposals were designed to work in a ge...

In the last years, serious games have been successfully exploited in different areas. However, in spite of the powerful tool that this kind of video games has proved to be in the classroom, a few methodological efforts have been conducted in order to involve pedagogues or educators in the design loop of these games or, one step further, include stu...

As part of the EDUBOTS Erasmus+ project, this paper is a small survey on technologies related to use of chatbots in the classroom and the expected outcomes of the pilot experience.

Bankruptcy is an issue of interest in the business world since decades. It is a crucial endeavor for survival to predict this phenomenon in periods of economic turmoil and recession. In fact, bankruptcy modeling is challenging due to the complexity of contributing factors and the highly imbalanced distribution of available data sets. This work aims...

The core challenge facing search techniques when used to play Real-Time Strategy (RTS) games is the extensive combinatorial decision space. Several approaches were proposed to alleviate this dimensionality burden, using scripts or action probability distributions, based on expert knowledge. We propose to replace expert-authored scripts with a colle...

The impressive performance of Monte Carlo Tree Search (MCTS) based game-playing agents in high branching-factor domains such as Go, motivated researchers to apply and adapt MCTS to even more challenging domains. Real-time strategy (RTS) games feature a large combinatorial branching factor and a real-time aspect that pose significant challenges to a...

This volume contains the Late-Breaking Abstracts submitted to the Evo* 2020 Conference, that took place online, from 15 to 17 of April 2020. These papers where presented as short talks and also at the poster session of the conference together with other regular submissions. All of them present ongoing research and preliminary results investigating...

General Videogame Playing is one of the hottest topics in the research field of AI in videogames. It aims at the implementation of algorithms or autonomous agents able to play a set of unknown games efficiently, just receiving the set of rules to play in real time. Thus, this work presents the implementation of eight approaches based on the main te...

One of the challenges of this century is to use the data that a smart-city provides to make life easier for its inhabitants. Specifically, within the area of urban mobility, the possibility of detecting anomalies in the movement of pedestrians and vehicles is an issue of vital importance for the planning and administration of a city. The aim of thi...

This paper presents the design and development of an Android application (using Unreal Engine 4) called GravityVolve. It is a two-dimensions game based on the N-Body problem previously presented by some of the authors. In order to complete a map, the player will have to push the particle from its initial position until it reaches the circumference’...

Online planning is an important research area focusing on the problem of real-time decision making, using information extracted from the environment. The aim is to compute, at each decision point, the best decision possible that contributes to the realization of a fixed objective. Relevant application domains include robotics, control engineering a...

Bankruptcy prediction problem is not new. Over the past 50 years, researchers have become increasingly interested in this problem , as it is a critical issue to forecast for companies. Taking this into account, in this work an efficient solution to the bankruptcy prediction problem is presented. To this end, a real dataset from Spanish companies ar...

This volume contains the Late-Breaking Abstracts submitted to the EVO* 2019 Conference, that took place in Leipzig, from 24 to 26 of April. These papers where presented as short talks and also at the poster session of the conference together with other regular submissions. All of them present ongoing research and preliminary results investigating o...

This paper presents an original approach based on evolutionary algorithms for building structures that are stable under gravity for the physics-based puzzle game Angry Birds, with the ultimate objective of creating Angry Birds levels with the minimum number of constraints. We have created a custom open source evolutionary computation library that i...

Bankruptcy is one of the most critical financial problems that reflects the company’s failure. From a machine learning perspective, the problem of bankruptcy prediction is considered a challenging one mainly because of the highly imbalanced distribution of the classes in the datasets. Therefore, developing an efficient prediction model that is able...

This paper presents a Java framework to implement dis-tributed applications via Bluetooth. It provides a high-level Application Programming Interface (API) which simplifies the creation of applica-tions for Bluetooth devices in Java ME and Java SE platforms. This framework is based in a client-server architecture and an event-driven asynchronous co...

This paper presents an original approach for building structures that are stable under gravity for the physics-based puzzle game Angry Birds, with the ultimate objective of creating levels with the minimum number of constraints. This approach consists of a search-based procedural level generation method that uses evolutionary algorithms. In order t...

Videogames are a very interesting area of research for fields as diverse as computer science, health, psychology or even social sciences. Every year a growing number of articles are published in different topics inside this field, so it is very convenient to study the different bibliometric data in order to consolidate the research efforts. Thus, t...

Resumen-Los simuladores de carreras de coches han sido utilizados durante mucho tiempo como un entorno para probar algoritmos de control autónomo de vehículos. Constituyen un entorno en el para evaluar todo tipo de algoritmos, incluyendo metaheurísticas, como por ejemplo Algoritmos Evolutivos. Sin embargo, el mayor desafío en este tipo de algoritmo...

The relevance of bankruptcy prediction problem is evident in today's world due to its effects on banks, businesses, and companies. There might be huge financial losses encountered due to bad judgment and analysis. Thus, in order to help improving the quality of such tasks, much efforts has been invested on building prediction models for aiding the...

In the context of the European Higher Education Area, it is needed to propose new motivation ways to engage university students in lectures. Since they prefer the application of active methodologies rather than passive ones, and they enjoy the use of interactive devices, using technology in the classroom seems promising. Thus, this paper presents a...

Algorithms for decision support in the battlefield have to take into account separately all factors with an impact of success: speed, visibility, and consumption of material and human resources. It is usual to combine several objectives, since military commanders give more importance to some factors than others, but it is interesting to also explor...

Bankruptcy is a critical financial problem that affects a high number of companies around the world. Thus, in recent years an increasing number of researchers have tried to solve it by applying different machine-learning models as powerful tools for the different economical agents related to the company. In this work, we propose the use of a simple...

Collectible card games have been among the most popular and profitable products of the entertainment industry since the early days of Magic: The GatheringTM in the nineties. Digital versions have also appeared, with HearthStone: Heroes of WarCraftTM being one of the most popular. In Hearthstone, every player can play as a hero, from a set of nine,...

This work presents an evolutionary approach to optimize the parameters of a Fuzzy-based autonomous driver for the open simulated car racing game (TORCS). Using evolutionary algorithms, we intend to optimize a modular fuzzy agent designed to determine the optimal target speed as well as the steering angle during the race. The challenge in this kind...

This paper introduces a procedure based on genetic pro-gramming to evolve XSLT programs (usually called stylesheets or logicsheets). XSLT is a general purpose, document-oriented functional language, generally used to transform XML doc-uments or, in general, solve any problem that can be coded as an XML document. The proposed solution uses a tree re...

Software development teams eventually become complex systems reaching a critical state, a fact that has already been proved by several researchers. This state, reached by self-organization, is characterized by three conditions applied to the sequence of changes: a scale-free structure, long-distance correlations, and so-called pink noise. In this p...

Dados los beneficios de un sistema de información sobre el estado del tráfico y del uso de la red viaria por parte de los vehículos, se plantea el desarrollo de un sistema de información de bajo coste para monitorizar el tráfico y conocer el estado de las carreteras en tiempo real. Los sistemas de información utilizados actualmente para la recopila...

This paper presents multiple hybridizations of the two best bots on the BotPrize 2014 competition, which sought for the best human-like bot playing the First Person Shooter game Unreal Tournament 2004. To this aim the participants were evaluated using a Turing test in the game. The work considers MirrorBot (the winner) and NizorBot (the second) cod...

When driving a car it is essential to take into account all possible factors; even more so when, like in the TORCS simulated race game, the objective is not only to avoid collisions, but also to win the race within a limited budget. In this paper, we present the design of an autonomous driver for racing car in a simulated race. Unlike previous cont...

This paper describes the application of a Wireless Traffic Monitoring and Tracking system in the Spanish city of Granada, as an approach for addressing important tasks in the field of Smart Traffic. To this end, several nodes of the so-called MOBYWIT system have been deployed at important urban points. They collect real-time vehicles’ movement info...

This paper presents a novel mobility monitoring system and some of its applications to address problems that would be solved in a Smart City, such as the optimization of traffic flows in terms of trip-time and security (Smart Traffic), and the improvement of security or energetic issues inside buildings. The system tracks the movement of people and...

When a new book is launched the publisher faces the problem of how many books should be printed for delivery to bookstores; printing too many is the main issue, since it implies a loss of investment due to inventory excess, but printing too few will also have a negative economic impact. In this paper, we are tackling the problem of predicting total...

One of the most notable features of collectible card games is deckbuilding, that is, defining a personalized deck before the real game. Deckbuilding is a challenge that involves a big and rugged search space, with different and unpredictable behaviour after simple card changes and even hidden information. In this paper, we explore the possibility o...

Finding the global best strategy for an autonomous agent (bot) in a RTS game is a hard problem, mainly because the techniques applied to do this must deal with uncertainty and real-time planning in order to control the game agents. This work describes an approach applying a Genetic Programming (GP) algorithm to create the behavioural engine of bots...

Detecting congestions on streets is one of the main issues in the area of smart cities. Regular monitoring methods can supply information about the number of vehicles in transit and thus the saturation of the streets, but they are usually expensive and intrusive with respect to the road. In recent years a new trend in traffic detection has arisen,...

This paper presents a mobility monitoring system, based on the detection of Bluetooth and WiFi signals emitted by personal portable devices. The work also describes its possibilities of tracking in two real scenarios, one inside the Spanish city of Granada, and another one in a highway between Granada and Málaga, both with several detection nodes....

Video game development is not only one of the most profitable entertainment industries but also represents a very interesting field of research. Particularly in the area of Artificial Intelligence (AI), it provides many interesting (and hard to tackle) challenges. One of them consists in creating artificial bots (i.e., game characters not controlle...

Simulation is a powerful and flexible technique for imitation of variety of stochastic processes and it has attractive advantages in comparison to analytical routine solutions. In this paper, the Monte Carlo simulation technique is used for imitation of operational process of electronic devices which is formalized by the model of Semi Markov proces...

This paper proposes an evolutionary algorithm for evolving game bots that eschews an explicit fitness function using instead a match between individuals called joust and implemented as a selection mechanism where only the winner survives. This algorithm has been designed as an optimization approach to generate the behavioural engine of bots for the...

This paper proposes an evolutionary algorithm for evolving game bots that eschews an explicit fitness function using instead a match between individuals called joust and implemented as a selection mechanism where only the winner survives. This algorithm has been designed as an optimization approach to generate the behavioural engine of bots for the...

Distributed Evolutionary Algorithms are traditionally executed on homogeneous dedicated clusters, despite most scientists have access mainly to networks of heterogeneous nodes (e.g., desktop PCs in a lab). Fitting this kind of algorithms to these environments, so that they can take advantage of their heterogeneity to save running time, is still an...

In most computer games as in life, the outcome of a match is uncertain due to several reasons: the characters or assets appear in different initial positions or the response of the player, even if programmed, is not deterministic; different matches will yield different scores. That is a problem when optimizing a game-playing engine: its fitness wil...

In many optimization processes, the fitness or the considered measure of goodness for the candidate solutions presents uncertainty, that is, it yields different values when repeatedly measured, due to the nature of the evaluation process or the solution itself. This happens quite often in the context of computational intelligence in games, when eit...

Corporate security is usually one of thematters in which companies invest more resources, since the loss of information directly translates intomonetary losses. Security issues might have an origin in external attacks or internal security failures, but an important part of the security breaches is related to the lack of awareness that the employees...

This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC) and Genetic Algorithms (GAs) and its application on a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing, and forecasting. They are, essentially, rule-based systems, i...

Among Real-Time Strategy games few titles have enjoyed the continued success of StarCraft. Many research lines aimed at developing Artificial Intelligences, or " bots " , capable of challenging human players, use StarCraft as a platform. Several characteristics make this game particularly appealing for researchers, such as: asymmetric balanced fact...

Companies and particularly their Chief Security Officers (CSOs) want to ensure that their Security Policies are followed, but this becomes a difficult goal to achieve at the point employees are able to use, or bring, their personal devices at work, in a practice that has been named "Bring Your Own Device" (BYOD). Since this BYOD philosophy is being...

Autonomous agents in videogames, usually called bots, have tried to behave as human players from their emergence more than 20 years ago. They normally try to model a part of a human expert player's knowledge with respect to the game, trying to become a competitive opponent or a good partner for other players. This paper presents a deep description...

Generating fiction environments for a multi-agent system optimized by genetic algorithms (with some specific requirements related to the desirable plots), presents two main problems: first it is impossible to know in advance the optimal value for the particular designed fitness function, and at the same time, it creates a vast search space for the...

Evolutionary Algorithms (EAs) are frequently used as a mechanism for the optimization of autonomous agents in games (bots), but knowing when to stop the evolution, when the bots are good enough, is not as easy as it would a priori seem. The first issue is that optimal bots are either unknown (and thus unusable as termination condition) or unreachab...

This paper proposes a methodology to design and implement Evolutionary Algorithms using the Service Oriented Architecture paradigm. This paradigm allows to deal with some of the shortcomings in the Evolutionary Algorithms area, facilitating the development, integration, standardization of services that conform a evolutionary algorithm, and, besides...