1,856 research outputs found

    Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

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    Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

    REDUCING OVERHEAD OF SELF-STABILIZING BYZANTINE AGREEMENT PROTOCOLS FOR BLOCKCHAIN USING HTTP/3 PROTOCOL: A PERSPECTIVE VIEW

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    Today, there is a tendency to reduce the dependence on local computation in favor of cloud computing. However, this inadvertently increases the reliance upon distributed fault-tolerant systems. In a condition that forced to work together, these systems often need to reach an agreement on some state or task, and possibly even in the presence of some misbehaving Byzantine nodes. Although non-trivial, Byzantine Agreement (BA) protocols now exist that are resilient to these types of faults. However, there is still a risk for inconsistencies in the application state in practice, even if a BA protocol is used. A single transient fault may put a node into an illegal state, creating a need for new self-stabilizing BA protocols to recover from illegal states. As self-stabilization often comes with a cost, primarily in the form of communication overhead, a potential lowering of latency - the cost of each message - could significantly impact how fast the protocol behaves overall. Thereby, there is a need for new network protocols such as QUIC, which, among other things, aims to reduce latency. In this paper, we survey current state-of-the-art agreement protocols. Based on previous work, some researchers try to implement pseudocode like QUIC protocol for Ethereum blockchain to have a secure network, resulting in slightly slower performance than the IP-based blockchain. We focus on consensus in the context of blockchain as it has prompted the development and usage of new open-source BA solutions that are related to proof of stake. We also discuss extensions to some of these protocols, specifically the possibility of achieving self-stabilization and the potential integration of the QUIC protocol, such as PoS and PBFT. Finally, further challenges faced in the field and how they might be overcome are discussed

    Cyber Security and Security Frameworks for Cloud and IoT Architectures

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    Das Cloud Computing hat die Art und Weise unserer Kommunikation in den letzten Jahren rapide verändert. Es ermöglicht die Bereitstellung unterschiedlicher Dienste über das Internet. Inzwischen wurden sowohl für Unternehmen, als auch für den privaten Sektor verschiedene Anwendungen des Cloud Computing entwickelt. Dabei bringt jede Anwendung zahlreiche Vorteile mit sich, allerdings werden auch neue Herausforderungen an die IT-Sicherheit gestellt. In dieser Dissertation werden besonders wichtige Anwendungen des Cloud Computing auf die aktuellen Herausforderungen für die IT-Sicherheit untersucht. 1. Die Container Virtualisierung ermöglicht die Trennung der eigentlichen Anwendung von der IT-Infrastruktur. Dadurch kann ein vorkonfiguriertes Betriebssystem-Image zusammen mit einer Anwendung in einem Container kombiniert und in einer Testumgebung evaluiert werden. Dieses Prinzip hat vor allem die Software-Entwicklung in Unternehmen grundlegend verändert. Container können verwendet werden, um software in einer isolierten Umgebung zu testen, ohne den operativen Betrieb zu stören. Weiterhin ist es möglich, verschiedene Container-Instanzen über mehrere Hosts hinweg zu verwalten. In dem Fall spricht man von einer Orchestrierung. Da Container sensible unternehmensinterne Daten beinhalten, müssen Unternehmen ihr IT-Sicherheitskonzept für den Einsatz von Container Virtualisierungen überarbeiten. Dies stellt eine große Herausforderung dar, da es derzeit wenig Erfahrung mit der Absicherung von (orchestrierten) Container Virtualisierungen gibt. 2. Da Container Dienste über das Internet bereitstellen, sind Mitarbeiterinnen und Mitarbeiter, die diese Dienste für ihre Arbeit benötigen, an keinen festen Arbeitsplatz gebunden. Dadurch werden wiederum Konzepte wie das home

    POET: an evo-devo method to optimize the weights of a large artificial neural networks

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    Large search spaces as those of artificial neural networks are difficult to search with machine learning techniques. The large amount of parameters is the main challenge for search techniques that do not exploit correlations expressed as patterns in the parameter space. Evolutionary computation with indirect genotype-phenotype mapping was proposed as a possible solution, but current methods often fail when the space is fractured and presents irregularities. This study employs an evolutionary indirect encoding inspired by developmental biology. Cellular proliferations and deletions of variable size allow for the definition of both regular large areas and small detailed areas in the parameter space. The method is tested on the search of the weights of a neural network for the classification of the MNIST dataset. The results demonstrate that even large networks such as those required for image classification can be effectively automatically designed by the proposed evolutionary developmental method. The combination of real-world problems like vision and classification, evolution and development, endows the proposed method with aspects of particular relevance to artificial life

    RTLabOS Dissemination Activities:RTLabOS D4.2

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    Computational Resource Abuse in Web Applications

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    Internet browsers include Application Programming Interfaces (APIs) to support Web applications that require complex functionality, e.g., to let end users watch videos, make phone calls, and play video games. Meanwhile, many Web applications employ the browser APIs to rely on the user's hardware to execute intensive computation, access the Graphics Processing Unit (GPU), use persistent storage, and establish network connections. However, providing access to the system's computational resources, i.e., processing, storage, and networking, through the browser creates an opportunity for attackers to abuse resources. Principally, the problem occurs when an attacker compromises a Web site and includes malicious code to abuse its visitor's computational resources. For example, an attacker can abuse the user's system networking capabilities to perform a Denial of Service (DoS) attack against third parties. What is more, computational resource abuse has not received widespread attention from the Web security community because most of the current specifications are focused on content and session properties such as isolation, confidentiality, and integrity. Our primary goal is to study computational resource abuse and to advance the state of the art by providing a general attacker model, multiple case studies, a thorough analysis of available security mechanisms, and a new detection mechanism. To this end, we implemented and evaluated three scenarios where attackers use multiple browser APIs to abuse networking, local storage, and computation. Further, depending on the scenario, an attacker can use browsers to perform Denial of Service against third-party Web sites, create a network of browsers to store and distribute arbitrary data, or use browsers to establish anonymous connections similarly to The Onion Router (Tor). Our analysis also includes a real-life resource abuse case found in the wild, i.e., CryptoJacking, where thousands of Web sites forced their visitors to perform crypto-currency mining without their consent. In the general case, attacks presented in this thesis share the attacker model and two key characteristics: 1) the browser's end user remains oblivious to the attack, and 2) an attacker has to invest little resources in comparison to the resources he obtains. In addition to the attack's analysis, we present how existing, and upcoming, security enforcement mechanisms from Web security can hinder an attacker and their drawbacks. Moreover, we propose a novel detection approach based on browser API usage patterns. Finally, we evaluate the accuracy of our detection model, after training it with the real-life crypto-mining scenario, through a large scale analysis of the most popular Web sites
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