Data mining and information extraction from data is a field that has gained relevance in recent years thanks to techniques based on artificial intelligence and use of machine and deep learning. The main aim of the present work is the development of a tool based on a previous behaviour study of security audit tools (oriented to SQL pentesting) with the purpose of creating testing sets capable of performing an accurate detection of a SQL attack. The study is based on the information collected through the generated web server logs in a pentesting laboratory environment. Then, making use of the common extracted patterns from the logs, each attack vector has been classified in risk levels (dangerous attack, normal attack, nonattack, etc.). Finally, a training with the generated data was performed in order to obtain a classifier system that has a variable performance between 97 and 99 percent in positive attack detection. The training data is shared to other servers in order to create a distributed network capable of deciding if a query is an attack or is a real petition and inform to connected clients in order to block the petitions from the attacker's IP.

This work presents a system to detect small boats (pateras) to help tackle the problem of this type of perilous immigration. The proposal makes extensive use of emerging technologies like Unmanned Aerial Vehicles (UAV) combined with a top-performing algorithm from the field of artificial intelligence known as Deep Learning through Convolutional Neural Networks. The use of this algorithm improves current detection systems based on image processing through the application of filters thanks to the fact that the network learns to distinguish the aforementioned objects through patterns without depending on where they are located. The main result of the proposal has been a classifier that works in real time, allowing the detection of pateras and people (who may need to be rescued), kilometres away from the coast. This could be very useful for Search and Rescue teams in order to plan a rescue before an emergency occurs. Given the high sensitivity of the managed information, the proposed system includes cryptographic protocols to protect the security of communications.

Communication media have become the primary way of interaction thanks to the discovery and innovation of many new technologies. One of the most widely used communication systems today is video streaming, which is constantly evolving. Such communications are a good alternative to face-to-face meetings, and are therefore very useful for coping with many problems caused by distance. However, they suffer from different issues such as bandwidth limitation, network congestion, energy efficiency, cost, reliability and connectivity. Hence, the quality of service and the quality of experience are considered the two most important issues for this type of communication. This work presents a complete comparative study of two of the most used protocols of video streaming, Real Time Streaming Protocol (RTSP) and the Web Real-Time Communication (WebRTC). In addition, this paper proposes two new mobile applications that implement those protocols in Android whose objective is to know how they are influenced by the aspects that most affect the streaming quality of service, which are the connection establishment time and the stream reception time. The new video streaming applications are also compared with the most popular video streaming applications for Android, and the experimental results of the analysis show that the developed WebRTC implementation improves the performance of the most popular video streaming applications with respect to the stream packet delay.

Huge losses and serious threats to ecosystems are common consequences of forest fires. This work describes a forest fire controller based on fuzzy logic and decision-making methods aiming at enhancing forest fire prevention, detection, and fighting systems. In the proposal, the environmental monitoring of several dynamic risk factors is performed with wireless sensor networks and analysed with the proposed fuzzy-based controller. With respect to this, meteorological variables, polluting gases and the oxygen level are measured in real time to estimate the existence of forest fire risks in the short-term and to detect the recent occurrence of fire outbreaks over different forest areas. Besides, the Analytic Hierarchy Process method is used to determine the level of fire spread, and, when necessary, environmental alerts are sent by a Web service and received by a mobile application. For this purpose, integrity, confidentiality, and authenticity of environmental information and alerts are protected with implementations of Lamport’s authentication scheme, Diffie-Lamport signature, and AES-CBC block cipher.

A vehicular ad hoc network (VANET) is a wireless network that provides communications between nearby vehicles. Among the different types of information that can be made available to vehicles through VANETs, road traffic information is the most important one. This work is part of an experimental development of a wireless communication platform oriented to applications that allow improving road efficiency and safety, managing and monitoring road traffic, encouraging cooperative driving, and offering pedestrian services and other added-value uses. The proposed system consists of smartphones, sensors, and Wi-Fi hotspots 2.0, as well as complementary functionalities including access to network infrastructure via 3G, GPRS, and 4G. The developed wireless network prototype allows taking advantage of the potential benefits of VANETs. At the same time, the use of smartphones does not require large money investments either in public or restricted areas. The first implementations with smartphones have been useful to test the behaviour of the proposal in a real environment. We have also implemented a large-scale simulation by using NS-2 simulator. From the obtained data, we have estimated the minimum requirements necessary for the correct working of a VANET and the problems that can happen in case of possible attacks or communication overhead.