Automatic Dataset Labelling and Feature Selection for Intrusion Detection Systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Correctly labelled datasets are commonly required. Three particular scenarios are highlighted, which showcase this need. When using supervised Intrusion Detection Systems (IDSs), these systems need labelled datasets to be trained. Also, the real nature of the analysed datasets must be known when evaluating the efficiency of the IDSs when detecting intrusions. Another scenario is the use of feature selection that works only if the processed datasets are labelled. In normal conditions, collecting labelled datasets from real networks is impossible. Currently, datasets are mainly labelled by implementing off-line forensic analysis, which is impractical because it does not allow real-time implementation. We have developed a novel approach to automatically generate labelled network traffic datasets using an unsupervised anomaly based IDS. The resulting labelled datasets are subsets of the original unlabelled datasets. The labelled dataset is then processed using a Genetic Algorithm (GA) based approach, which performs the task of feature selection. The GA has been implemented to automatically provide the set of metrics that generate the most appropriate intrusion detection results

A look into the information your smartphone leaks

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Some smartphone applications (apps) pose a risk to users’ personal information. Events of apps leaking information stored in smartphones illustrate the danger that they present. In this paper, we investigate the amount of personal information leaked during the installation and use of apps when accessing the Internet. We have opted for the implementation of a Man-in-the-Middle proxy to intercept the network traffic generated by 20 popular free apps installed on different smartphones of distinctive vendors. This work describes the technical considerations and requirements for the deployment of the monitoring WiFi network employed during the conducted experiments. The presented results show that numerous mobile and personal unique identifiers, along with personal information are leaked by several of the evaluated apps, commonly during the installation process

Adding Contextual Information to Intrusion Detection Systems Using Fuzzy Cognitive Maps

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In the last few years there has been considerable increase in the efficiency of Intrusion Detection Systems (IDSs). However, networks are still the victim of attacks. As the complexity of these attacks keeps increasing, new and more robust detection mechanisms need to be developed. The next generation of IDSs should be designed incorporating reasoning engines supported by contextual information about the network, cognitive information and situational awareness to improve their detection results. In this paper, we propose the use of a Fuzzy Cognitive Map (FCM) in conjunction with an IDS to incorporate contextual information into the detection process. We have evaluated the use of FCMs to adjust the Basic Probability Assignment (BPA) values defined prior to the data fusion process, which is crucial for the IDS that we have developed. The experimental results that we present verify that FCMs can improve the efficiency of our IDS by reducing the number of false alarms, while not affecting the number of correct detections

Un juego de espejos: Venises

In this article, we study the book Venises by the French diplomat, voyager and writer Paul Morand. Using the concept of mixed speech, we will unveil the peculiarities of this work related to the author’s own life (autobiographic speech), to his vocation for books about trips and cities (descriptive speech), and with his perception of Venice as a mythical city, built through memory and the world of art and culture (literary speech).En el presente articulo se examina la obra Venises del diplomatico, viajero y escritor frances Paul Morand. A traves del concepto de discurso mixto, se pondran de manifiesto las peculiaridades de esta obra en relacion con la vida del propio autor (discurso autobiografico), con su vocacion por los libros sobre viajes y ciudades (discurso descriptivo) y con su percepcion de Venecia como ciudad mitica, fabricada a traves del recuerdo, del mundo del arte y de la cultura (discurso literario)

Instituciones políticas, procesos de diseño de políticas y resultados de las políticas en México

(Disponible en idioma inglés únicamente) En este trabajo se emplea un marco de costos de transacción para vincular el proceso de diseño de políticas (PMP, por sus siglas en inglés) y las características externas de las políticas públicas en México, un país en desarrollo con ingresos medios. Se muestra cómo un PMP altamente secreto y centralizado alrededor de la Presidencia produjo políticas de corte nacionalista que fueron estables, adaptables, coordinadas y consideradas para con el sector privado radicado en las ciudades y que constituye el soporte corporativista del régimen. Sin embargo, cuando el crecimiento flaqueó a finales de los años 70, este PMP no pudo adaptarse a la inestabilidad económica, aunque mantuvo su vigor en un cuerpo político cada vez más inquieto. El documento explica cómo un gobierno unificado y el control corporativista de la economía convirtieron a un presidente constitucionalmente débil en la envidia de ejecutivos de todo el mundo, incluso a costa de no poder promulgar reformas que resultaren costosas a corto plazo para los pilares corporativistas del régimen. El artículo también explica por qué la democratización durante los años 90 está dando pie a un PMP menos centralizado y más abierto, que beneficie a un sector más amplio de la población. A medida que se materializa la separación de poderes consagrada en la Constitución de 1917, el diseño de políticas se va entretejiendo cada vez más con el status quo. Por otro lado, un gobierno dividido conserva un marco macroeconómico que se corresponde con una economía abierta (como por ejemplo, políticas fiscalmente prudentes y un tipo de cambio flotante). Por otro lado, los frenos y contrapesos están ayudando a partidos nuevos y viejos y a grupos de intereses a obstaculizar la confluencia de voluntades en cuanto al aumento de impuestos crónicamente bajos (10% del PIB) y sobre la reforma de políticas nacionalistas que restrinjan la inversión del sector privado en el sector energético controlado por el Estado.

Using metrics from multiple layers to detect attacks in wireless networks

The IEEE 802.11 networks are vulnerable to numerous wireless-specific attacks. Attackers can implement MAC address spoofing techniques to launch these attacks, while masquerading themselves behind a false MAC address. The implementation of Intrusion Detection Systems has become fundamental in the development of security infrastructures for wireless networks. This thesis proposes the designing a novel security system that makes use of metrics from multiple layers of observation to produce a collective decision on whether an attack is taking place. The Dempster-Shafer Theory of Evidence is the data fusion technique used to combine the evidences from the different layers. A novel, unsupervised and self- adaptive Basic Probability Assignment (BPA) approach able to automatically adapt its beliefs assignment to the current characteristics of the wireless network is proposed. This BPA approach is composed of three different and independent statistical techniques, which are capable to identify the presence of attacks in real time. Despite the lightweight processing requirements, the proposed security system produces outstanding detection results, generating high intrusion detection accuracy and very low number of false alarms. A thorough description of the generated results, for all the considered datasets is presented in this thesis. The effectiveness of the proposed system is evaluated using different types of injection attacks. Regarding one of these attacks, to the best of the author knowledge, the security system presented in this thesis is the first one able to efficiently identify the Airpwn attack

Full Paper: Blockchain Technology Adoption: Factors Influencing Intention and Usage

Blockchain technology is already being discussed as an emerging trend for the upcoming years. Researchers and organizations are beginning to recognize the potential benefits of this technology and are exploring how it can disrupt our world. However, the reality is that there has not been much progress in getting blockchain from a concept to widespread adoption. This study aimed to investigate the factors that influence the adoption of blockchain technology. We proposed a model that incorporated relevant features to blockchain technology adoption, specifically the role of Trust and Security as mediating variables. Data was collected using a questionnaire administered to people working in companies independently of their technology usage. Structural equation modeling using partial least squares (SEM-PLS) was used to analyze the data and construct the model. Results indicated that performance expectancy, social influence, and trust positively influenced people’s actual use or intention to adopt blockchain technology. Additionally, environmental concerns had a negative effect on the intention to adopt. These findings suggest that individuals are more likely to adopt blockchain technology when they perceive it as valuable and trustworthy and receive support from their social networks

Support Vector Machine for Network Intrusion and Cyber-Attack Detection

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Cyber-security threats are a growing concern in networked environments. The development of Intrusion Detection Systems (IDSs) is fundamental in order to provide extra level of security. We have developed an unsupervised anomaly-based IDS that uses statistical techniques to conduct the detection process. Despite providing many advantages, anomaly-based IDSs tend to generate a high number of false alarms. Machine Learning (ML) techniques have gained wide interest in tasks of intrusion detection. In this work, Support Vector Machine (SVM) is deemed as an ML technique that could complement the performance of our IDS, providing a second line of detection to reduce the number of false alarms, or as an alternative detection technique. We assess the performance of our IDS against one-class and two-class SVMs, using linear and non-linear forms. The results that we present show that linear two-class SVM generates highly accurate results, and the accuracy of the linear one-class SVM is very comparable, and it does not need training datasets associated with malicious data. Similarly, the results evidence that our IDS could benefit from the use of ML techniques to increase its accuracy when analysing datasets comprising of non-homogeneous features

Factors Influencing Intention and Usage

Cesario, F., Costa, C. J., Aparicio, M., & Aparicio, J. T. (2023). Blockchain Technology Adoption: Factors Influencing Intention and Usage. In A. R. da Silva, M. M. da Silva, J. Estima, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development, Organizational Aspects and Societal Trends (ISD2023 Proceedings) Instituto Superior Técnico. https://aisel.aisnet.org/isd2014/proceedings2023/managingdevops/1/ --- Funding: The authors acknowledge financial support via ADVANCE- CSG from the Fundação para a Ciência and Tecnologia (FCT Portugal) through research grant numbers UIDB/04521/2020; research grant UIDB/04152/2020—Centro de Investigação em Gestão de Informação (MagIC); and research grant UI/BD/153587/2022.Blockchain technology is already being discussed as an emerging trend for the upcoming years. Researchers and organizations are beginning to recognize the potential benefits of this technology and are exploring how it can disrupt our world. However, the reality is that there has not been much progress in getting blockchain from a concept to widespread adoption. This study aimed to investigate the factors that influence the adoption of blockchain technology. We proposed a model that incorporated relevant features to blockchain technology adoption, specifically the role of Trust and Security as mediating variables. Data was collected using a questionnaire administered to people working in companies independently of their technology usage. Structural equation modeling using partial least squares (SEM-PLS) was used to analyze the data and construct the model. Results indicated that performance expectancy, social influence, and trust positively influenced people’s actual use or intention to adopt blockchain technology. Additionally, environmental concerns had a negative effect on the intention to adopt. These findings suggest that individuals are more likely to adopt blockchain technology when they perceive it as valuable and trustworthy and receive support from their social networks.authorsversionpublishe

Aplicación de medidas indirectas de exposición al análisis del riesgo de accidente

El número de víctimas en accidentes de tráfico se ha descompuesto tradicionalmente en tres dimensiones: exposición; riesgo de accidente, definido como el número de accidentes por unidad de exposición; y riesgo de lesión, definido como el número de víctimas por cada accidente. Hasta el momento, el conocimiento sobre los factores que influyen sobre el riesgo de accidente es deficiente, un hecho relacionado con la extraordinaria dificultad para obtener información sobre la exposición de distintos grupos de usuarios y vehículo