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The knowledge of the topological structure and the automatic fare collection systems in urban public transport produce many data that need to be adequately analyzed, processed and presented. These data provide a powerful tool to improve the quality of transport services and plan ahead. This paper aims at studying, from a mathematical and statistical point of view, the Barcelona metro network; specifically: (1) the structural and robustness characteristics of the transportation network are computed and analyzed considering the complex network analysis; and (2) the common characteristics of the different subway stations of Barcelona, based on the passenger hourly entries, are identified through hierarchical clustering analysis. These results will be of great help in planning and restructuring transport to cope with the new social conditions, after the pandemic.
Irene Mariñas-Collado; Elisa Frutos Bernal; Maria Santos Martin; Angel Martín del Rey; Roberto Casado Vara; Ana Gil-González. A Mathematical Study of Barcelona Metro Network. Electronics 2021, 10, 557 .
AMA StyleIrene Mariñas-Collado, Elisa Frutos Bernal, Maria Santos Martin, Angel Martín del Rey, Roberto Casado Vara, Ana Gil-González. A Mathematical Study of Barcelona Metro Network. Electronics. 2021; 10 (5):557.
Chicago/Turabian StyleIrene Mariñas-Collado; Elisa Frutos Bernal; Maria Santos Martin; Angel Martín del Rey; Roberto Casado Vara; Ana Gil-González. 2021. "A Mathematical Study of Barcelona Metro Network." Electronics 10, no. 5: 557.
Evaluating web traffic on a web server is highly critical for web service providers since, without a proper demand forecast, customers could have lengthy waiting times and abandon that website. However, this is a challenging task since it requires making reliable predictions based on the arbitrary nature of human behavior. We introduce an architecture that collects source data and in a supervised way performs the forecasting of the time series of the page views. Based on the Wikipedia page views dataset proposed in a competition by Kaggle in 2017, we created an updated version of it for the years 2018–2020. This dataset is processed and the features and hidden patterns in data are obtained for later designing an advanced version of a recurrent neural network called Long Short-Term Memory. This AI model is distributed training, according to the paradigm called data parallelism and using the Downpour training strategy. Predictions made for the seven dominant languages in the dataset are accurate with loss function and measurement error in reasonable ranges. Despite the fact that the analyzed time series have fairly bad patterns of seasonality and trend, the predictions have been quite good, evidencing that an analysis of the hidden patterns and the features extraction before the design of the AI model enhances the model accuracy. In addition, the improvement of the accuracy of the model with the distributed training is remarkable. Since the task of predicting web traffic in as precise quantities as possible requires large datasets, we designed a forecasting system to be accurate despite having limited data in the dataset. We tested the proposed model on the new Wikipedia page views dataset we created and obtained a highly accurate prediction; actually, the mean absolute error of predictions regarding the original one on average is below 30. This represents a significant step forward in the field of time series prediction for web traffic forecasting.
Roberto Casado-Vara; Angel Martin del Rey; Daniel Pérez-Palau; Luis De-La-Fuente-Valentín; Juan Corchado. Web Traffic Time Series Forecasting Using LSTM Neural Networks with Distributed Asynchronous Training. Mathematics 2021, 9, 421 .
AMA StyleRoberto Casado-Vara, Angel Martin del Rey, Daniel Pérez-Palau, Luis De-La-Fuente-Valentín, Juan Corchado. Web Traffic Time Series Forecasting Using LSTM Neural Networks with Distributed Asynchronous Training. Mathematics. 2021; 9 (4):421.
Chicago/Turabian StyleRoberto Casado-Vara; Angel Martin del Rey; Daniel Pérez-Palau; Luis De-La-Fuente-Valentín; Juan Corchado. 2021. "Web Traffic Time Series Forecasting Using LSTM Neural Networks with Distributed Asynchronous Training." Mathematics 9, no. 4: 421.
Machine Learning has recently emerged as a new paradigm for processing all types of information. In particular, Artificial Intelligence is attractive to corporations & research institutions as it provides innovative solutions for unsolved problems, & it enjoys a great popularity among the general public. However, despite the fact that Machine Learning offers huge opportunities for the IT industry, Artificial Intelligence technology is still at its infancy, with many issues to be addressed. In this paper, we present a survey of quaternion applications in Neural Networks, one of the most promising research lines in artificial vision which also has a great potential in several other topics. The aim of this paper is to provide a better understanding of the design challenges of Quaternion Neural Networks & identify important research directions in this increasingly important area.
David García-Retuerta; Roberto Casado-Vara; Angel Martin-Del Rey; Fernando De La Prieta; Javier Prieto; Juan M. Corchado. Quaternion Neural Networks: State-of-the-Art and Research Challenges. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 456 -467.
AMA StyleDavid García-Retuerta, Roberto Casado-Vara, Angel Martin-Del Rey, Fernando De La Prieta, Javier Prieto, Juan M. Corchado. Quaternion Neural Networks: State-of-the-Art and Research Challenges. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():456-467.
Chicago/Turabian StyleDavid García-Retuerta; Roberto Casado-Vara; Angel Martin-Del Rey; Fernando De La Prieta; Javier Prieto; Juan M. Corchado. 2020. "Quaternion Neural Networks: State-of-the-Art and Research Challenges." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 456-467.
Traceability and monitoring of industrial processes are becoming more important to assure the value of final products. Blockchain technology emerged as part of a movement linked to criptocurrencies and the Internet of Things, providing nice-to-have features such as traceability, authenticity and security to sectors willing to use this technology. In the retail industry, blockchain offers users the possibility to monitor details about time and place of elaboration, the origin of raw materials, the quality of materials involved in the manufacturing processes, information on the people or companies that work on it, etc. It allows to control and monitor textile articles, from their production or importing initial steps, up to their acquisition by the end consumer, using the blockchain as a means of tracking and identification during the whole process. This technology can also be used by the apparel industry in general and, more specifically, for ready-to-wear clothing, for tracing suppliers and customers along the entire logistics chain. The goal of this paper is to introduce the more recent traceability schemes for the apparel industry together with the proposal of a framework for ready-to-wear clothing which allows to ensure the transparency in the supply chain, clothing authenticity, reliability and integrity, and validity of the retail final products, and of the elements that compose the whole supply chain. In order to illustrate the proposal, a case study on a women’s shirt from an apparel and fashion company, where a private and open blockchain is used for tracing the product, is included. Blockchain actors are proposed for each product stage.
Juan Bullón Pérez; Araceli Queiruga-Dios; Víctor Gayoso Martínez; Ángel Martín Del Rey. Traceability of Ready-to-Wear Clothing through Blockchain Technology. Sustainability 2020, 12, 7491 .
AMA StyleJuan Bullón Pérez, Araceli Queiruga-Dios, Víctor Gayoso Martínez, Ángel Martín Del Rey. Traceability of Ready-to-Wear Clothing through Blockchain Technology. Sustainability. 2020; 12 (18):7491.
Chicago/Turabian StyleJuan Bullón Pérez; Araceli Queiruga-Dios; Víctor Gayoso Martínez; Ángel Martín Del Rey. 2020. "Traceability of Ready-to-Wear Clothing through Blockchain Technology." Sustainability 12, no. 18: 7491.
An important way considered to control malware epidemic processes is to take into account security measures that are associated to the systems of ordinary differential equations that governs the dynamics of such systems. We can observe two types of control measures: the analysis of the basic reproductive number and the study of control measure functions. The first one is taken at the beginning of the epidemic process and, therefore, we can consider this to be a prevention measure. The second one is taken during the epidemic process. In this work, we use the theory of optimal control that is associated to systems of ordinary equations in order to find a new function to control malware epidemic through time. Specifically, this approach is evaluate on a particular compartmental malware model that considers carrier devices.
Jose Hernández Guillén; Ángel Martín Del Rey; Roberto Casado Vara. On the Optimal Control of a Malware Propagation Model. Mathematics 2020, 8, 1518 .
AMA StyleJose Hernández Guillén, Ángel Martín Del Rey, Roberto Casado Vara. On the Optimal Control of a Malware Propagation Model. Mathematics. 2020; 8 (9):1518.
Chicago/Turabian StyleJose Hernández Guillén; Ángel Martín Del Rey; Roberto Casado Vara. 2020. "On the Optimal Control of a Malware Propagation Model." Mathematics 8, no. 9: 1518.
Ensuring air quality should be a mandatory premise in every building, since if not, its occupants are on high risk. In fact, Radon pollutants are stated to be the second main cause among all lung cancer patients in the United States. Radon is a noble gas which seeps up through the ground and accumulates there, making it hard to be identified. A proper ventilation system needs to be installed on industrial plants so that the Radon exhaled from building materials is properly dispelled, ensuring fresh, quality air. In order to keep a proper air quality level in smart buildings, a control ventilation strategy should be defined so that the exhaled Radon is ensured to be dispelled keeping the indoor air quality high. In the proposed paper, the diffusion-advecntion method has been studied in order to propose a solution on Radon concentration tracing on smart buildings ventilation system. Diffusion-advecntion is a mathematical method that will determine whether Radon will propagate or not, based on the concentration of Radon, the diffusion constant and the advecntion velocity of the indoor air, which can lead to a recommendation for the smart building ventilation system to be activated or not, respectively. In this paper a new ventilation strategy for smart buildings based on the Diffusion-advecntion equation has been proposed to improve air quality. The results of this new ventilation strategy have been tested in a real case study in a smart building in the city of Salamanca. The main outcome of this new strategy is the improvement in response times of the current systems.
Roberto Casado-Vara; David García-Retuerta; Alvaro Bartolomé; Esteban Jove; Jose Luis Calvo-Rolle; Angel Martin-Del Rey; Juan M. Corchado. Demand Control Ventilation Strategy by Tracing the Radon Concentration in Smart Buildings. Advances in Intelligent Systems and Computing 2020, 374 -382.
AMA StyleRoberto Casado-Vara, David García-Retuerta, Alvaro Bartolomé, Esteban Jove, Jose Luis Calvo-Rolle, Angel Martin-Del Rey, Juan M. Corchado. Demand Control Ventilation Strategy by Tracing the Radon Concentration in Smart Buildings. Advances in Intelligent Systems and Computing. 2020; ():374-382.
Chicago/Turabian StyleRoberto Casado-Vara; David García-Retuerta; Alvaro Bartolomé; Esteban Jove; Jose Luis Calvo-Rolle; Angel Martin-Del Rey; Juan M. Corchado. 2020. "Demand Control Ventilation Strategy by Tracing the Radon Concentration in Smart Buildings." Advances in Intelligent Systems and Computing , no. : 374-382.
The aim of this work is to introduce and analyze an novel SCIRS model for malware propagation that considers different infection rates for both infectious and carrier devices. This model is an improvement of a former theoretical model where infectious and carrier have the same behavior in the infection phase. The proposed model is mathematically studied and some important conclusions about its behavior are derived. Moreover, efficient security countermeasures are obtained from the analysis of the basic reproductive number, and a brief comparison with the former model is presented.
Jose Diamantino Hernández Guillén; Angel Martín Del Rey. Simulating Malware Propagation with Different Infection Rates. Proceedings of the 2nd International Conference on Data Engineering and Communication Technology 2020, 253 -262.
AMA StyleJose Diamantino Hernández Guillén, Angel Martín Del Rey. Simulating Malware Propagation with Different Infection Rates. Proceedings of the 2nd International Conference on Data Engineering and Communication Technology. 2020; ():253-262.
Chicago/Turabian StyleJose Diamantino Hernández Guillén; Angel Martín Del Rey. 2020. "Simulating Malware Propagation with Different Infection Rates." Proceedings of the 2nd International Conference on Data Engineering and Communication Technology , no. : 253-262.
The concept of smart cities emerged in the 1990s. Since then, smart buildings have become a closely interconnected element of smart cities. This type of building implements Internet of Things technology and control algorithms to monitor and control their indoor environment. The aim of this paper is to develop a new stability criterion method for smart building Internet of Things (IoT) systems, subject to external disturbances. The new stability criterion is going to optimize the operation of control algorithms since this criterion does not depend on the transmission function of the control algorithm but on the data collected by the IoT system. We present a new matrix called “Laplacian IoT matrix”, containing IoT network information associated with the graph of a smart building. The proposal is supported by the results of a numerical case study.
Roberto Casado-Vara; Angel Martín Del Rey; Ricardo Alonso; Saber Trabelsi; Juan Corchado. A New Stability Criterion for IoT Systems in Smart Buildings: Temperature Case Study. Mathematics 2020, 8, 1412 .
AMA StyleRoberto Casado-Vara, Angel Martín Del Rey, Ricardo Alonso, Saber Trabelsi, Juan Corchado. A New Stability Criterion for IoT Systems in Smart Buildings: Temperature Case Study. Mathematics. 2020; 8 (9):1412.
Chicago/Turabian StyleRoberto Casado-Vara; Angel Martín Del Rey; Ricardo Alonso; Saber Trabelsi; Juan Corchado. 2020. "A New Stability Criterion for IoT Systems in Smart Buildings: Temperature Case Study." Mathematics 8, no. 9: 1412.
With the growth of cities, urban traffic has increased and traffic congestion has become a serious problem. Due to their characteristics, metro systems are one of the most used public transportation networks in big cities. So, optimization and planning of metro networks are challenges which governments must focus on. The objective of this study was to analyze Madrid metro network using graph theory. Through complex network theory, the main structural and topological properties of the network as well as robustness characteristics were obtained. Furthermore, to inspect these results, multivariate analysis techniques were employed, specifically HJ-Biplot. This analysis tool allowed us to explore relationships between centrality measures and to classify stations according to their centrality. Therefore, it is a multidisciplinary study that includes network analysis and multivariate analysis. The study found that closeness and eccentricity were strongly negatively correlated. In addition, the most central stations were those located in the city center, that is, there is a relationship between centrality and geographic location. In terms of robustness, a highly agglomerated community structure was found.
E. Frutos Bernal; A. Martín Del Rey; P. Galindo Villardón. Analysis of Madrid Metro Network: From Structural to HJ-Biplot Perspective. Applied Sciences 2020, 10, 5689 .
AMA StyleE. Frutos Bernal, A. Martín Del Rey, P. Galindo Villardón. Analysis of Madrid Metro Network: From Structural to HJ-Biplot Perspective. Applied Sciences. 2020; 10 (16):5689.
Chicago/Turabian StyleE. Frutos Bernal; A. Martín Del Rey; P. Galindo Villardón. 2020. "Analysis of Madrid Metro Network: From Structural to HJ-Biplot Perspective." Applied Sciences 10, no. 16: 5689.
In this work the notion of linear cellular automata on trees with loops is introduced and the reversibility problem in some particular cases is tackled. The explicit expressions of the inverse cellular automata are computed.
A. Martín Del Rey; E. Frutos Bernal; D. Hernández Serrano; R. Casado Vara. The Reversibility of Cellular Automata on Trees with Loops. Advances in Intelligent Systems and Computing 2020, 241 -250.
AMA StyleA. Martín Del Rey, E. Frutos Bernal, D. Hernández Serrano, R. Casado Vara. The Reversibility of Cellular Automata on Trees with Loops. Advances in Intelligent Systems and Computing. 2020; ():241-250.
Chicago/Turabian StyleA. Martín Del Rey; E. Frutos Bernal; D. Hernández Serrano; R. Casado Vara. 2020. "The Reversibility of Cellular Automata on Trees with Loops." Advances in Intelligent Systems and Computing , no. : 241-250.
Epilepsy is one of the most invalidating neurological conditions, affecting 1\(\%\) of the global population. The main diagnostic tool for epilepsy is electroencephalography (EEG), used to detect local field potentials and discern pathological brain patterns, i.e., ictal activity (the EEG correlate of a clinical seizure) and interictal activity (the pathological brain pattern occurring between seizures). Interictal activity may provide insights into seizure generation mechanisms and may contain information relevant to the identification of the seizure onset zone. Further, interictal activity may be relevant for seizure prediction algorithms. This paper presents a algorithm for accurate detection of interictal events using a combination of mathematical methods.
David García-Retuerta; Angel Canal-Alonso; Roberto Casado-Vara; Angel Martin-Del Rey; Gabriella Panuccio; Juan M. Corchado. Bidirectional-Pass Algorithm for Interictal Event Detection. Robotics in Education 2020, 197 -204.
AMA StyleDavid García-Retuerta, Angel Canal-Alonso, Roberto Casado-Vara, Angel Martin-Del Rey, Gabriella Panuccio, Juan M. Corchado. Bidirectional-Pass Algorithm for Interictal Event Detection. Robotics in Education. 2020; ():197-204.
Chicago/Turabian StyleDavid García-Retuerta; Angel Canal-Alonso; Roberto Casado-Vara; Angel Martin-Del Rey; Gabriella Panuccio; Juan M. Corchado. 2020. "Bidirectional-Pass Algorithm for Interictal Event Detection." Robotics in Education , no. : 197-204.
Failure mode and effects analysis (FMEA) is an important technique in safety and reliability analysis, which has been widely used to identify and eliminate known or potential failure. In the process of evaluating failure modes (FMs), experts usually adopt different types of linguistic information to reflect their judgments, and the weights of experts or criteria are often incompletely known. This study aims to develop a novel approach to solve heterogeneous linguistic FMEA problem, in which the ratings of FMs are described by different types of linguistic information, and the information about the importance of experts and criteria is incomplete. Firstly, we propose a linguistic distribution assessment Shapley Choquet ordered averaging (LDASCOA) operator, and discuss some properties of the operator, such as idempotency, monotonicity, boundary and commutativity. Secondly, we present a new idea to convert different types of linguistic information to linguistic distribution assessments (LDAs). Thirdly, to obtain collective linguistic distribution assessment decision matrix and necessary weights, we construct a model to determine the optimal fuzzy measures on expert set with respect to each criterion considering the interactions among elements in the expert set. Fourthly, a new approach to determine the priority of FMs is proposed by defining linguistic distribution assessment ideal variate (LDAIV) and linguistic distribution assessment nadir variate (LDANV), as well as calculating the relative correlation coefficient of each failure. Finally, an illustrative example is given to demonstrate the calculation process of the developed approach, and the advantages are verified by comparing the evaluation result of the developed approach with that of existing methods.
Yanbing Ju; Yuanyuan Liang; Martínez Luis; Aihua Wang; Chen-Fu Chien; Peiwu Dong; Ernesto D.R. Santibanez Gonzalez. A new approach for heterogeneous linguistic failure mode and effect analysis with incomplete weight information. Computers & Industrial Engineering 2020, 148, 106659 .
AMA StyleYanbing Ju, Yuanyuan Liang, Martínez Luis, Aihua Wang, Chen-Fu Chien, Peiwu Dong, Ernesto D.R. Santibanez Gonzalez. A new approach for heterogeneous linguistic failure mode and effect analysis with incomplete weight information. Computers & Industrial Engineering. 2020; 148 ():106659.
Chicago/Turabian StyleYanbing Ju; Yuanyuan Liang; Martínez Luis; Aihua Wang; Chen-Fu Chien; Peiwu Dong; Ernesto D.R. Santibanez Gonzalez. 2020. "A new approach for heterogeneous linguistic failure mode and effect analysis with incomplete weight information." Computers & Industrial Engineering 148, no. : 106659.
An advanced persistent threat (APT) can be defined as a targeted and very sophisticated cyber attack. IT administrators need tools that allow for the early detection of these attacks. Several approaches have been proposed to provide solutions to this problem based on the attack life cycle. Recently, machine learning techniques have been implemented in these approaches to improve the problem of detection. This paper aims to propose a new approach to APT detection, using machine learning techniques, and is based on the life cycle of an APT attack. The proposed model is organised into two passive stages and three active stages to adapt the mitigation techniques based on machine learning.
Santiago Quintero-Bonilla; Angel Martín Del Rey. A New Proposal on the Advanced Persistent Threat: A Survey. Applied Sciences 2020, 10, 3874 .
AMA StyleSantiago Quintero-Bonilla, Angel Martín Del Rey. A New Proposal on the Advanced Persistent Threat: A Survey. Applied Sciences. 2020; 10 (11):3874.
Chicago/Turabian StyleSantiago Quintero-Bonilla; Angel Martín Del Rey. 2020. "A New Proposal on the Advanced Persistent Threat: A Survey." Applied Sciences 10, no. 11: 3874.
The choice of suitable health-care waste disposal alternative (HCWDA) is critical to health-care waste management and has recently attracted much attention for both researchers and practitioners. During the evaluation of HCWDA, there usually exists incomplete and uncertain information, and the experts cannot easily express their judgments on the alternatives with precise values. This paper presents a new framework based on the evaluation based on distance from average solution (EDAS) method for selecting desirable health-care waste disposal alternative(s). Multi-granular linguistic distribution assessments are adopted by experts to assess the ratings of alternatives and subjective weights of criteria. To reflect accurately the reality, an approach is firstly proposed to determine the experts’ weights with respect to each criterion based on Dice similarity measure. Secondly, to determine the objective weights of criteria a combination of the minimum variance and the maximizing deviation methods are introduced, from it the comprehensive weights of criteria will be derived. Thirdly, the traditional EDAS method is extended to rank and select reasonable HCWDA. Finally, a numerical example of the proposed framework is provided, and its validity is verified by comparing it with previous methods.
Yanbing Ju; Yuanyuan Liang; Martínez Luis; Ernesto D.R. Santibanez Gonzalez; Mihalis Giannakis; Peiwu Dong; Aihua Wang. A new framework for health-care waste disposal alternative selection under multi-granular linguistic distribution assessment environment. Computers & Industrial Engineering 2020, 145, 106489 .
AMA StyleYanbing Ju, Yuanyuan Liang, Martínez Luis, Ernesto D.R. Santibanez Gonzalez, Mihalis Giannakis, Peiwu Dong, Aihua Wang. A new framework for health-care waste disposal alternative selection under multi-granular linguistic distribution assessment environment. Computers & Industrial Engineering. 2020; 145 ():106489.
Chicago/Turabian StyleYanbing Ju; Yuanyuan Liang; Martínez Luis; Ernesto D.R. Santibanez Gonzalez; Mihalis Giannakis; Peiwu Dong; Aihua Wang. 2020. "A new framework for health-care waste disposal alternative selection under multi-granular linguistic distribution assessment environment." Computers & Industrial Engineering 145, no. : 106489.
In this work a novel model to simulate advanced malware spreading is introduced and analyzed. It is an individual-based model such that the dynamics of the malware outbreak is governed by means of a cellular automaton. The network topologies considered are complex random networks and each device is endowed at every step of time with one of the following possible states: susceptible, infected, attacked and recovered. A study analyzing the influence of topology variability and the structural characteristics of initially infected devices is done.
A. Martín del Rey; G. Hernández; A. Bustos Tabernero; A. Queiruga Dios. Advanced malware propagation on random complex networks. Neurocomputing 2020, 423, 689 -696.
AMA StyleA. Martín del Rey, G. Hernández, A. Bustos Tabernero, A. Queiruga Dios. Advanced malware propagation on random complex networks. Neurocomputing. 2020; 423 ():689-696.
Chicago/Turabian StyleA. Martín del Rey; G. Hernández; A. Bustos Tabernero; A. Queiruga Dios. 2020. "Advanced malware propagation on random complex networks." Neurocomputing 423, no. : 689-696.
Wireless Sensor Networks (WSNs) are a set of sensor devices deployed in a given area that form a network without a pre-established architecture. Recently, malware has increased as a potential vulnerability for the Internet of Things, and consequently for these networks. The spread of malware on wireless sensor networks has been studied from different perspectives, excluding individual characteristics in most of the models proposed. The primary goal of this work is to introduce an Agent-Based Model for analysing malware propagation on these networks, and its agents, coefficients and transition rules are detailed. Finally, some simulations of the proposed model are included.
Farrah Kristel Batista; Angel Martín Del Rey; Araceli Queiruga-Dios. A New Individual-Based Model to Simulate Malware Propagation in Wireless Sensor Networks. Mathematics 2020, 8, 410 .
AMA StyleFarrah Kristel Batista, Angel Martín Del Rey, Araceli Queiruga-Dios. A New Individual-Based Model to Simulate Malware Propagation in Wireless Sensor Networks. Mathematics. 2020; 8 (3):410.
Chicago/Turabian StyleFarrah Kristel Batista; Angel Martín Del Rey; Araceli Queiruga-Dios. 2020. "A New Individual-Based Model to Simulate Malware Propagation in Wireless Sensor Networks." Mathematics 8, no. 3: 410.
The aim of this work is to describe and analyze a new theoretical model to simulate the spread of malicious code on wireless sensor networks. Specifically, this is a SCIRS model such that population dynamics, and vaccination and reinfection processes are considered. The local and global stability of the equilibrium points are studied and the most important security countermeasures are explicitly shown by means of the analysis of the epidemic threshold.
J.D. Hernández Guillén; A. Martín Del Rey. A mathematical model for malware spread on WSNs with population dynamics. Physica A: Statistical Mechanics and its Applications 2019, 545, 123609 .
AMA StyleJ.D. Hernández Guillén, A. Martín Del Rey. A mathematical model for malware spread on WSNs with population dynamics. Physica A: Statistical Mechanics and its Applications. 2019; 545 ():123609.
Chicago/Turabian StyleJ.D. Hernández Guillén; A. Martín Del Rey. 2019. "A mathematical model for malware spread on WSNs with population dynamics." Physica A: Statistical Mechanics and its Applications 545, no. : 123609.
Internet of Things (IoT) is the paradigm that has largely contributed to the development of smart buildings in our society. This technology makes it possible to monitor all aspects of the smart building and to improve its operation. One of the main challenges encountered by IoT networks is that the the data they collect may be unreliable since IoT devices can lose accuracy for several reasons (sensor wear, sensor aging, poorly constructed buildings, etc.). The aim of our work is to study the evolution of IoT networks over time in smart buildings. The hypothesis we have tested is that, by amplifying the Lotka–Volterra equations as a community of living organisms (an ecosystem model), the reliability of the system and its components can be predicted. This model comprises a set of differential equations that describe the relationship between an IoT network and multiple IoT devices. Based on the Lotka–Volterra model, in this article, we propose a model in which the predators are the non-precision IoT devices and the prey are the precision IoT devices. Furthermore, a third species is introduced, the maintenance staff, which will impact the interaction between both species, helping the prey to survive within the ecosystem. This is the first Lotka–Volterra model that is applied in the field of IoT. Our work establishes a proof of concept in the field and opens a wide spectrum of applications for biology models to be applied in IoT.
Roberto Casado-Vara; Angel Canal-Alonso; Angel Martin-Del Rey; Fernando De La Prieta; Javier Prieto. Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model. Sensors 2019, 19, 4642 .
AMA StyleRoberto Casado-Vara, Angel Canal-Alonso, Angel Martin-Del Rey, Fernando De La Prieta, Javier Prieto. Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model. Sensors. 2019; 19 (21):4642.
Chicago/Turabian StyleRoberto Casado-Vara; Angel Canal-Alonso; Angel Martin-Del Rey; Fernando De La Prieta; Javier Prieto. 2019. "Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka–Volterra Ecosystem Model." Sensors 19, no. 21: 4642.
In the new and sophisticated cyber attacks (mainly, advanced persistent threats) the advanced specimens of malware such that zero-day malware play a crucial role. Due to its stealthy behavior it is very important to study and analyze its propagation process by designing mathematical models that could predict in an efficient way its spread on a network. With no doubt the computational implementation of these theoretical models leads to the develop of solutions to be used in the Security Operation Centers (SOC) with forensic purposes. The main goal of this work is to introduce a novel mathematical model to simulate advanced malware. Specifically, it is a compartmental and global SCIRAS (Susceptible-Carrier-Infectious-Recovered-Attacked-Susceptible) model where susceptible, carrier, infectious, recovered and attacked devices are considered. The local and global stability of its equilibrium points are studied and the basic reproductive number is computed. From the analysis of this epidemiological threshold, the most efficient security countermeasures are derived.
J. D. Hernandez Guillen; A. Martin del Rey; Roberto Casado-Vara. Security Countermeasures of a SCIRAS Model for Advanced Malware Propagation. IEEE Access 2019, 7, 135472 -135478.
AMA StyleJ. D. Hernandez Guillen, A. Martin del Rey, Roberto Casado-Vara. Security Countermeasures of a SCIRAS Model for Advanced Malware Propagation. IEEE Access. 2019; 7 (99):135472-135478.
Chicago/Turabian StyleJ. D. Hernandez Guillen; A. Martin del Rey; Roberto Casado-Vara. 2019. "Security Countermeasures of a SCIRAS Model for Advanced Malware Propagation." IEEE Access 7, no. 99: 135472-135478.
The aim of this work is to completely solve the reversibility problem for symmetric linear cellular automata with radius r = 3 and null boundary conditions. The main result obtained is the explicit computation of the local transition functions of the inverse cellular automata. This allows introduction of possible and interesting applications in digital image encryption.
A. Martín Del Rey; R. Casado Vara; D. Hernández Serrano. Reversibility of Symmetric Linear Cellular Automata with Radius r = 3. Mathematics 2019, 7, 816 .
AMA StyleA. Martín Del Rey, R. Casado Vara, D. Hernández Serrano. Reversibility of Symmetric Linear Cellular Automata with Radius r = 3. Mathematics. 2019; 7 (9):816.
Chicago/Turabian StyleA. Martín Del Rey; R. Casado Vara; D. Hernández Serrano. 2019. "Reversibility of Symmetric Linear Cellular Automata with Radius r = 3." Mathematics 7, no. 9: 816.