Constant ransomware attacks achieve to evade multiple security perimeters, because its strategy is based on the exploitation of users-the weakest link in the security chain-getting high levels of effectiveness. In this paper, an in-depth analysis of the anatomy of the ransomware is develop, and how they combine technology with manipulation, through social engineering, to meet their goals and compromise thousands of computers. Finally, simulations of the phases that it follows are carried out, leaving the necessary guidelines to evaluate the security of the information, and thus, generate policies that minimize the risks of loss of information.

At present, the constant development of information and communication technologies (ICTs) is allowing the creation of applications and services that require the automated and individualized deployment of resources on the network. However, the traditional or inherited infrastructure presents innovation difficulties as a consequence of the cost that its adaptation would imply, therefore it is necessary to find alternatives that efficiently manage the existing resources. A new paradigm arises based on the decoupling of the control plane from the data plane of each device to place it in a centralized entity, giving way to the use of software-based technologies. This paper proposes the implementation of a wide area network defined by software (SD-WAN) to connect two data centers defined by software, which guarantees a predefined quality of service (QoS) and traffic prioritization. Several simulations are carried out in scenarios governed by VoIP services and bandwidth, delay, jitter and CPU load are measured. Among the results obtained, the validity of the mentioned solutions is demonstrated.

Vehicular ad hoc networks (VANETs) face challenges related to the reliability of the data exchanged and the unstability of the communication links. These shortcomings have hampered the development of the long-awaited applications that would turn roads into a smart environment. We present a framework to deploy such services, in which a virtualization layer ensures means to efficiently deliver messages between vehicles and roadside units (RSUs) and, on top of that, blockchain technology is used to enable features of data integrity, traceability, and reliability that cannot be furnished by existing consensus and reputation mechanisms. A simulation experiment is included to determine the optimal number of RSUs to be installed as supporting infrastructure in a city.

In this article a process of animation of 3D models is proposed to transform them into virtual agents or avatars with the possibility of being used in Human-Computer interaction processes. The resulting virtual agents have been adapted as tools that serve as a starting point for the development of real-time interaction algorithms. The characteristics of the generated tools allows to deepen in techniques of machine learning and artificial intelligence, endowing to the virtual agents of movements with natural and real characteristics. It is possible to use them as puppets, capturing the movements of a person and transferring them to the animation; it is also possible to program specific sequences whose interaction processes are completely determined. Finally, the idea of developing algorithms involving artificial intelligence combined with human intelligence to improve interaction processes is proposed.

In this article we present a study of different models with fractal geometry implemented in Ultra Wide-Band (UWB) antennas design. With different methods and geometric variants applied to this type of antennas, frequency ranges between 1-20GHz are obtained, generating an efficiency greater than 90% in its operating band, considering the variation of different parameters such as iterations, shape, slots, among other things; Bandwidths greater than 15GHz have been achieved, this has generated a wide range of applications for fractal antennas. An analysis was carried out based on the similarity of the models, the operating ranges, and the constructive characteristics, with the aim of improving bandwidth, efficiency, and radiation properties, generating options that will serve as a starting point for the development and design of antennas in the future.

In this article we present a general review of nature-inspired metaheuristic algorithms with implementations in patch antenna designs. The primary focus is on Genetic Algorithm (GA), Differential Evolution (DE), Particle Swarm Optimization (PSO), Bacterial Foraging Optimization (BFO). New algorithms recently been introduced also are analyzed, such as: Firefly algorithm (FA), Cuckoo Search (CS), Bat algorithm (BA), Social Spider Optimization (SSO) and Spider Monkey Optimization (SMO). Of each algorithm, a summary of significant examples and a flowchart for a quick and easy interpretation are presented. Finally, the common characteristics of algorithms are compared, concluding in a hierarchical classification according to the efficiency of each one to solve the patch antenna problems.