Search

La Lightning Network (LN) és una xarxa de pagament que pot operar sobre Bitcoin i que podria potencialment processar infinitat de pagaments de manera simultània. Però és vulnerable. Investigadors de la UAB han detectat que és possible fer un atac que bloqueja els canals de pagament. La Lightning Network (LN) es una red de pago que puede operar sobre Bitcoin y que podría potencialmente procesar infinidad de pagos de forma simultánea. Pero es vulnerable. Investigadores de la UAB han detectado que es posible llevar a cabo un ataque que bloquea los canales de pago. The Lightning Network (LN) is a payment network that can operate on top of Bitcoin and could potentially process countless payments simultaneously. But it is vulnerable. UAB researchers have detected that it is possible to carry out an attack that blocks payment channels.

Aquest projecte mostra com les connexions dels usuaris d'una xarxa social suposen un risc afegit per a la privacitat dels usuaris que hi formen part. Aquestes connexions ofereixen informació suficient per a poder dur a terme processos d'agregació d'informació entre diferents xarxes socials, permetent a un atacant millorar el seu coneixement inicial sobre les xarxes. El projecte és un recorregut per totes les fases necessàries per dur a terme aquest procés, des de la recollida de la informació fins a l'agregació de les dades obtingudes. Este proyecto muestra como las conexiones de los usuarios de una red social suponen un riesgo añadido para la privacidad de los usuarios que la forman. Estas conexiones ofrecen información suficiente para poder realizar procesos de agregación de información entre diferentes redes sociales, permitiendo a un atacante mejorar su conocimiento inicial sobre las redes. El proyecto es un recorrido por las diversas fases necesarias para realizar este proceso, desde la recogida de información hasta la agregación de los datos obtenidos. This project shows that link connections in social networks suppose a new risk for user's privacy. These links provide an attacker with enough information to make aggregation processes between different online social networks, improving the attackers initial knowledge of the network. This project is a journey towards this aggregation process, starting from data collection and ending in the aggregation itself.

International audience; This book constitutes the refereed conference proceedings of the 14th International Workshop on Data Privacy Management, DPM 2019, and the Third International Workshop on Cryptocurrencies and Blockchain Technology, CBT 2019, held in conjunction with the 24th European Symposium on Research in Computer Security, ESORICS 2019, held in Luxembourg in September 2019. For the CBT Workshop 10 full and 8 short papers were accepted out of 39 submissions. The selected papers are organized in the following topical headings: lightning networks and level 2; smart contracts and applications; and payment systems, privacy and mining. The DPM Workshop received 26 submissions from which 8 full and 2 short papers were selected for presentation. The papers focus on privacy preserving data analysis; field/lab studies; and privacy by design and data anonymization. Chapter 2, “Integral Privacy Compliant Statistics Computation,” and Chapter 8, “Graph Perturbation as Noise Graph Addition: a New Perspective for Graph Anonymization,” of this book are available open access under a CC BY 4.0 license at link.springer.com.

Solidity smart contracts operate in a hostile environment, which introduces the need for the adequate application of testing techniques to ensure mitigation of the risk of a security incident. Mutation testing is one such technique. It allows for the evaluation of the efficiency of a test suite in detecting faults in a program, allowing developers to both assess and improve the quality of their test suites. In this paper, we propose a mutation testing framework and implement a prototype implementation called Vertigo that targets Solidity contracts for the Ethereum blockchain. We also show that mutation testing can be used to assess the test suites of real-world projects.

La enseñanza de la programación en el ámbito universitario, a pesar de toda la experiencia acumulada, presenta muchos retos aún por alcanzar. Son diversos los elementos que añaden complejidad a este empeño y diversos también los estudios y propuestas didácticas que se proponen para abordarlos. El reto es aún mayor desde que, recientemente, se han incorporado al panorama universitario nuevos programas de especialidad con asignaturas de programación en ámbitos multidisciplinares como la bioinformática o la ciencia de datos. En este artículo se describe la experiencia de dos asignaturas de nivel de máster: “Programación para la bioinformática” y “Programación para la Ciencia de Datos”, ambas introductorias a la programación en el lenguaje Python, pero orientadas cada una de ellas a la resolución de los problemas específicos que se plantean en cada uno de estos dos ámbitos. Se trata de un objetivo tremendamente complejo, sobre todo si tenemos en cuenta el perfil heterogéneo de entrada de los estudiantes, poco o nada acostumbrados a la programación. In the university context and despite all the accumulated experience over the past decades, teaching computer programming is still challenging. The different approaches to accomplish this goal are diverse and complex, with many different didactic proposals. New challenges have aroused in recent times with the development of new and more specialized courses for multidisciplinary programs, such as bioinformatics or data science. In this work we describe the experience obtained in two MSc programs: Programming for Bioinformatics and Programming for Data Science, both of them with an introductory aim at programming in the Python language and oriented to solve specific problems and challenges in the two different scopes. This is an extremely complex goal, considering the heterogeneous background of the students, not familiar with coding.

© 2018 Elsevier Ltd Third-party applications on Facebook can collect personal data of the users who install them, but also of their friends. This raises serious privacy issues as these friends are not notified by the applications nor by Facebook and they have not given consent. This paper presents a detailed multi-faceted study on the collateral information collection of the applications on Facebook. To investigate the views of the users, we designed a questionnaire and collected the responses of 114 participants. The results show that participants are concerned about the collateral information collection and in particular about the lack of notification and of mechanisms to control the data collection. Based on real data, we compute the likelihood of collateral information collection affecting users: we show that the probability is significant and greater than 80% for popular applications such as TripAdvisor. We also demonstrate that a substantial amount of profile data can be collected by applications, which enables application providers to profile users. To investigate whether collateral information collection is an issue to users’ privacy we analysed the legal framework in light of the General Data Protection Regulation. We provide a detailed analysis of the entities involved and investigate which entity is accountable for the collateral information collection. To provide countermeasures, we propose a privacy dashboard extension that implements privacy scoring computations to enhance transparency toward collateral information collection. Furthermore, we discuss alternative solutions highlighting other countermeasures such as notification and access control mechanisms, cryptographic solutions and application auditing. To the best of our knowledge this is the first work that provides a detailed multi-faceted study of this problem and that analyses the threat of user profiling by application providers. ispartof: Computers & Security vol:77 pages:179-208 status: published

P2P networks are the mechanism used by cryptocurrencies to disseminate system information while keeping the whole system as much decentralized as possible. Cryptocurrency P2P networks have new characteristics that propose new challenges and avoid some problems of existing P2P networks. By characterizing the most relevant cryptocurrency network, Bitcoin, we provide details on different properties of cryptocurrency networks and their similarities and differences with standard P2P network paradigms. Our study allows us to conclude that cryptocurrency networks present a new paradigm of P2P networks due to the mechanisms they use to achieve high resilience and security. With this new paradigm, interesting research lines can be further developed, both in the focused field of P2P cryptocurrency networks and also when such networks are combined with other distributed scenarios.