Implantación de plataforma virtual en prácticas docentes interuniversitarias en el Internet de las Cosas

Las titulaciones compartidas e impartidas por distintas instituciones universitarias están cobrando gran auge, ya que permiten aunar esfuerzos y ofrecer títulos interdisciplinares que aprovechan la sinergia entre profesorado diverso. No obstante, la descentralización de los estudiantes conlleva el reto de mantener la calidad y homogeneidad de la docencia en todas las instituciones implicadas, especialmente en las sesiones prácticas. Por este motivo, en este trabajo se propone una metodología docente en una asignatura de Internet de las Cosas en un máster interuniversitario impartido por dos centros españoles, que requiere tratar con grupos de estudiantes heterogéneos y material para prácticas distinto en ambas sedes. Se ha desarrollado un sistema de prácticas presenciales y virtuales que es común para el alumnado de ambas instituciones, de modo que ambos grupos realizan las mismas sesiones aun no disponiendo de un equipamiento de prácticas homogéneo. Las prácticas tienen un enfoque técnico, incluyendo el montaje y programación de circuitos electrónicos con Arduino y su interconexión con una plataforma de Internet de las Cosas en la nube. Mientras que los estudiantes presenciales tienen acceso a los componentes hardware del sistema a desplegar, los que asisten en remoto realizan el mismo montaje a través de una plataforma de simulación on-line, permitiendo desarrollos equivalentes y un seguimiento homogéneo en el ejercicio docente. La propuesta se encuentra actualmente en fase de ejecución y este trabajo presenta sus principales características, identificando los retos para los siguientes cursos académicos.The degrees shared by different universities are gaining momentum lately. They allow to combine efforts and offer interdisciplinary degrees to students, taking advantage of the synergy among diverse teaching staff. However, the decentralization of students brings the challenge of maintaining quality and homogeneity of education, especially in practical sessions. For this reason, this paper proposes a teaching methodology in a subject focused on the Internet of Things (IoT). This subject is framed in an interuniversity master taught by two Spanish centers, which requires dealing with heterogeneous students and equipment for practices in both venues. Therefore, a common laboratory program has been developed for the students of both institutions, so that both groups perform the same laboratory sessions even if they do not have a homogeneous equipment. The practices have an eminent technical approach, including the assembly and programming of electronic circuits with Arduino and its interconnection with an IoT platform in the cloud. While the face-to-face students have access to the real hardware components, those who attend remotely do the same work through an on-line simulation platform, allowing equivalent developments and a homogeneous follow-up of sessions. The proposed teaching methodology is currently in its execution phase and this paper presents its main features, identifying major challenges for the coming years.Este trabajo ha sido realizado con el soporte del proyecto PERSEIDES (TIN2017-86885-R) del Ministerio de Economía, Industria y Competitividad, del Programa Ramón y Cajal (RYC-2017-23823) del Misterio de Ciencia, Innovación y Universidades, así como del programa “Ayudas para la Excelencia de los Equipos de Investigación Avanzada en Ciberseguridad“ del INCIBE (INCIBEI-2015-27363)

Research challenges in nextgen service orchestration

Fog/edge computing, function as a service, and programmable infrastructures, like software-defined networking or network function virtualisation, are becoming ubiquitously used in modern Information Technology infrastructures. These technologies change the characteristics and capabilities of the underlying computational substrate where services run (e.g. higher volatility, scarcer computational power, or programmability). As a consequence, the nature of the services that can be run on them changes too (smaller codebases, more fragmented state, etc.). These changes bring new requirements for service orchestrators, which need to evolve so as to support new scenarios where a close interaction between service and infrastructure becomes essential to deliver a seamless user experience. Here, we present the challenges brought forward by this new breed of technologies and where current orchestration techniques stand with regards to the new challenges. We also present a set of promising technologies that can help tame this brave new world

Defining the Behavior of IoT Devices through the MUD Standard : Review, Challenges, and Research Directions

With the strong development of the Internet of Things (IoT), the definition of IoT devices' intended behavior is key for an effective detection of potential cybersecurity attacks and threats in an increasingly connected environment. In 2019, the Manufacturer Usage Description (MUD) was standardized within the IETF as a data model and architecture for defining, obtaining and deploying MUD files, which describe the network behavioral profiles of IoT devices. While it has attracted a strong interest from academia, industry, and Standards Developing Organizations (SDOs), MUD is not yet widely deployed in real-world scenarios. In this work, we analyze the current research landscape around this standard, and describe some of the main challenges to be considered in the coming years to foster its adoption and deployment. Based on the literature analysis and our own experience in this area, we further describe potential research directions exploiting the MUD standard to encourage the development of secure IoT-enabled scenarios

Distributed Security Framework for Reliable Threat Intelligence Sharing

Computer security incident response teams typically rely on threat intelligence platforms for information about sightings of cyber threat events and indicators of compromise. Other security building blocks, such as Network Intrusion Detection Systems, can leverage the information to prevent malicious adversaries from spreading malware across critical infrastructures. The effectiveness of threat intelligence platforms heavily depends on the willingness to share among organizations and the responsible use of sensitive information that may potentially harm the reputation of the reporting organization. The challenge that we address is the lack of trust in the source providing the threat intelligence and the information itself. We enhance our security framework TATIS—offering fine-grained protection for threat intelligence platform APIs—with distributed ledger capabilities to enable reliable and trustworthy threat intelligence sharing with the ability to audit the provenance of threat intelligence. We have implemented and evaluated the feasibility of our distributed framework on top of the Malware Information Sharing Platform (MISP) solution, and we evaluate the performance impact using real-world open-source threat intelligence feeds.status: Published onlin

Distributed Security Framework for Reliable Threat Intelligence Sharing

Computer security incident response teams typically rely on threat intelligence platforms for information about sightings of cyber threat events and indicators of compromise. Other security building blocks, such as Network Intrusion Detection Systems, can leverage the information to prevent malicious adversaries from spreading malware across critical infrastructures. The effectiveness of threat intelligence platforms heavily depends on the willingness to share among organizations and the responsible use of sensitive information that may potentially harm the reputation of the reporting organization. The challenge that we address is the lack of trust in the source providing the threat intelligence and the information itself. We enhance our security framework TATIS—offering fine-grained protection for threat intelligence platform APIs—with distributed ledger capabilities to enable reliable and trustworthy threat intelligence sharing with the ability to audit the provenance of threat intelligence. We have implemented and evaluated the feasibility of our distributed framework on top of the Malware Information Sharing Platform (MISP) solution, and we evaluate the performance impact using real-world open-source threat intelligence feeds