Hyperloop: A Cybersecurity Perspective

Hyperloop is among the most prominent future transportation systems. First introduced by Elon Musk, Hyperloop concept involves novel technologies to allow traveling at a maximum speed of 1220km/h, while guaranteeing sustainability. Due to the system's performance requirements and the critical infrastructure it represents, its safety and security need to be carefully considered. In cyber-physical systems, cyberattacks could lead to safety issues with catastrophic consequences, both on the population and the surrounding environment. Therefore, the cybersecurity of all the components and links in Hyperloop represents a fundamental challenge. To this day, no research investigated the cyber security of the technology used for Hyperloop. In this paper, we propose the first analysis of the cybersecurity challenges raised by Hyperloop technology. We base our analysis on the related works on Hyperloop, distilling the common features which will be likely to be present in the system. Furthermore, we provide an analysis of possible directions on the Hyperloop infrastructure management, together with their security concerns. Finally, we discuss possible countermeasures and future directions for the security of the future Hyperloop design.Comment: 9 pages, 4 figures, 1 tabl

Project BeARCAT : Baselining, Automation and Response for CAV Testbed Cyber Security : Connected Vehicle & Infrastructure Security Assessment

Connected, software-based systems are a driver in advancing the technology of transportation systems. Advanced automated and autonomous vehicles, together with electrification, will help reduce congestion, accidents and emissions. Meanwhile, vehicle manufacturers see advanced technology as enhancing their products in a competitive market. However, as many decades of using home and enterprise computer systems have shown, connectivity allows a system to become a target for criminal intentions. Cyber-based threats to any system are a problem; in transportation, there is the added safety implication of dealing with moving vehicles and the passengers within

Threat vector analysis in autonomous driving

Σημείωση: διατίθεται συμπληρωματικό υλικό σε ξεχωριστό αρχείο

Robust and secure resource management for automotive cyber-physical systems

2022 Spring.Includes bibliographical references.Modern vehicles are examples of complex cyber-physical systems with tens to hundreds of interconnected Electronic Control Units (ECUs) that manage various vehicular subsystems. With the shift towards autonomous driving, emerging vehicles are being characterized by an increase in the number of hardware ECUs, greater complexity of applications (software), and more sophisticated in-vehicle networks. These advances have resulted in numerous challenges that impact the reliability, security, and real-time performance of these emerging automotive systems. Some of the challenges include coping with computation and communication uncertainties (e.g., jitter), developing robust control software, detecting cyber-attacks, ensuring data integrity, and enabling confidentiality during communication. However, solutions to overcome these challenges incur additional overhead, which can catastrophically delay the execution of real-time automotive tasks and message transfers. Hence, there is a need for a holistic approach to a system-level solution for resource management in automotive cyber-physical systems that enables robust and secure automotive system design while satisfying a diverse set of system-wide constraints. ECUs in vehicles today run a variety of automotive applications ranging from simple vehicle window control to highly complex Advanced Driver Assistance System (ADAS) applications. The aggressive attempts of automakers to make vehicles fully autonomous have increased the complexity and data rate requirements of applications and further led to the adoption of advanced artificial intelligence (AI) based techniques for improved perception and control. Additionally, modern vehicles are becoming increasingly connected with various external systems to realize more robust vehicle autonomy. These paradigm shifts have resulted in significant overheads in resource constrained ECUs and increased the complexity of the overall automotive system (including heterogeneous ECUs, network architectures, communication protocols, and applications), which has severe performance and safety implications on modern vehicles. The increased complexity of automotive systems introduces several computation and communication uncertainties in automotive subsystems that can cause delays in applications and messages, resulting in missed real-time deadlines. Missing deadlines for safety-critical automotive applications can be catastrophic, and this problem will be further aggravated in the case of future autonomous vehicles. Additionally, due to the harsh operating conditions (such as high temperatures, vibrations, and electromagnetic interference (EMI)) of automotive embedded systems, there is a significant risk to the integrity of the data that is exchanged between ECUs which can lead to faulty vehicle control. These challenges demand a more reliable design of automotive systems that is resilient to uncertainties and supports data integrity goals. Additionally, the increased connectivity of modern vehicles has made them highly vulnerable to various kinds of sophisticated security attacks. Hence, it is also vital to ensure the security of automotive systems, and it will become crucial as connected and autonomous vehicles become more ubiquitous. However, imposing security mechanisms on the resource constrained automotive systems can result in additional computation and communication overhead, potentially leading to further missed deadlines. Therefore, it is crucial to design techniques that incur very minimal overhead (lightweight) when trying to achieve the above-mentioned goals and ensure the real-time performance of the system. We address these issues by designing a holistic resource management framework called ROSETTA that enables robust and secure automotive cyber-physical system design while satisfying a diverse set of constraints related to reliability, security, real-time performance, and energy consumption. To achieve reliability goals, we have developed several techniques for reliability-aware scheduling and multi-level monitoring of signal integrity. To achieve security objectives, we have proposed a lightweight security framework that provides confidentiality and authenticity while meeting both security and real-time constraints. We have also introduced multiple deep learning based intrusion detection systems (IDS) to monitor and detect cyber-attacks in the in-vehicle network. Lastly, we have introduced novel techniques for jitter management and security management and deployed lightweight IDSs on resource constrained automotive ECUs while ensuring the real-time performance of the automotive systems

From Resilience-Building to Resilience-Scaling Technologies: Directions -- ReSIST NoE Deliverable D13

This document is the second product of workpackage WP2, "Resilience-building and -scaling technologies", in the programme of jointly executed research (JER) of the ReSIST Network of Excellence. The problem that ReSIST addresses is achieving sufficient resilience in the immense systems of ever evolving networks of computers and mobile devices, tightly integrated with human organisations and other technology, that are increasingly becoming a critical part of the information infrastructure of our society. This second deliverable D13 provides a detailed list of research gaps identified by experts from the four working groups related to assessability, evolvability, usability and diversit

Diseño de una ciudad inteligente para redes vehiculares

English: road safety has become a main issue for governments and car manufacturers in the last twenty years. The development of new vehicular technologies has favored companies, researchers and institutions to focus their efforts on improving road safety. During the last decades, the evolution of wireless technologies has allowed researchers to design communication systems where vehicles participate in the communication networks. Thus, the concept of Intelligent Transportation Systems (ITS) appeared. This concept is used when talking about communication technologies between vehicles and infrastructure that improve transport safety, its management, environmental performance, etc. Due to the high economic cost of real-life tests and experimentation, the use of simulators becomes really useful when developing ITS. Nonetheless, simulators not always include all the capabilities needed to simulate these kinds of networks. Thus, in this project the NCTUns simulator is modified in order to add new capabilities that allow users simulate ITS. Furthermore, smart city scenarios are simulated in order to evaluate how the use of these networks allows real-time statistic collection and calculation, and how modifications made in NCTUns work.Castellano: la seguridad en la carretera se ha convertido en un problema principal para gobiernos y fabricantes de automóviles en los últimos años. El desarrollo de nuevas tecnologías vehiculares ha permitido a compañías, investigadores e instituciones a centrar sus esfuerzos para mejorar la seguridad vial. Durante las últimas décadas, la evolución de la tecnología de comunicación inalámbrica ha permitido a investigadores el diseño de sistemas de comunicación en los cuales los vehículos forman parte de la red de comunicación. De esta forma, se creó el concepto de Sistema de Transporte Inteligente (STI), concepto utilizado al hablar sobre las tecnologías de comunicación entre vehículos e infraestructura, que mejoran la seguridad vial en el transporte, su mejor gestión, eficiencia medioambiental, etc. Debido al alto coste económico de probar STI en situaciones reales, el uso de simuladores es realmente útil a la hora de desarrollar este tipo de sistemas. Así, en este proyecto el simulador NCTUns ha sido modificado con el objetivo de añadir nuevas posibilidades al simulador que ayuden a diseñar STI. Además, un escenario de una ciudad inteligente ha sido simulado con el objetivo de evaluar como el uso de estas redes permite la recolección y el cálculo de estadísticas en tiempo real, además de comprobar cómo funcionan los cambios realizados en el simulador.Català: la seguretat a la carretera ha esdevingut un problema principal pels governs i pels fabricants d'automòbils en els últims anys. El desenvolupament de noves tecnologies de vehicles ha afavorit a les empreses, els investigadors i les institucions que centrin els seus esforços a millorar la seguretat viària. Durant les últimes dècades, l'evolució de les tecnologies sense fils ha permès als investigadors a dissenyar sistemes de comunicació on els vehicles poden participar en les xarxes de comunicació. D'aquesta manera, es crea el concepte de Sistema de Transport Intel·ligent (STI), concepte utilitzat en parlar sobre les tecnologies de comunicació entre vehicles i infraestructura que milloren la seguretat vial en el transport, la seva millor gestió, l'eficiència mediambiental, etc. A causa de l'alt cost econòmic de provar STI en situacions reals, l'ús de simuladors és realment útil a l'hora de desenvolupar STI. Així, en aquest projecte el simulador NCTUns ha estat modificat amb l'objectiu d'afegir noves possibilitats al simulador que ajudin a dissenyar STI a futurs usuaris. A més, un escenari d'una ciutat intel·ligent ha estat simulat amb l'objectiu d'avaluar com l'ús de la xarxa permet la recol·lecció i el càlcul d'estadístiques en temps real, a més de comprovar com funcionen els canvis realitzats en el simulador

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words

CACIC 2015 : XXI Congreso Argentino de Ciencias de la Computación. Libro de actas

Actas del XXI Congreso Argentino de Ciencias de la Computación (CACIC 2015), realizado en Sede UNNOBA Junín, del 5 al 9 de octubre de 2015.Red de Universidades con Carreras en Informática (RedUNCI

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions