23,207 research outputs found
A Critical Look at Decentralized Personal Data Architectures
While the Internet was conceived as a decentralized network, the most widely
used web applications today tend toward centralization. Control increasingly
rests with centralized service providers who, as a consequence, have also
amassed unprecedented amounts of data about the behaviors and personalities of
individuals.
Developers, regulators, and consumer advocates have looked to alternative
decentralized architectures as the natural response to threats posed by these
centralized services. The result has been a great variety of solutions that
include personal data stores (PDS), infomediaries, Vendor Relationship
Management (VRM) systems, and federated and distributed social networks. And
yet, for all these efforts, decentralized personal data architectures have seen
little adoption.
This position paper attempts to account for these failures, challenging the
accepted wisdom in the web community on the feasibility and desirability of
these approaches. We start with a historical discussion of the development of
various categories of decentralized personal data architectures. Then we survey
the main ideas to illustrate the common themes among these efforts. We tease
apart the design characteristics of these systems from the social values that
they (are intended to) promote. We use this understanding to point out numerous
drawbacks of the decentralization paradigm, some inherent and others
incidental. We end with recommendations for designers of these systems for
working towards goals that are achievable, but perhaps more limited in scope
and ambition
Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments
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
Strategies and challenges to facilitate situated learning in virtual worlds post-Second Life
Virtual worlds can establish a stimulating environment to support a situated learning approach in which students simulate a task within a safe environment. While in previous years Second Life played a major role in providing such a virtual environment, there are now more and more alternative—often OpenSim-based—solutions deployed within the educational community. By drawing parallels to social networks, we discuss two aspects: how to link individually hosted virtual worlds together in order to implement context for immersion and how to identify and avoid “fake” avatars so people behind these avatars can be held accountable for their actions
Analyzing the impact of storage shortage on data availability in decentralized online social networks
Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs). The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today’s online social networks (OSNs) due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction
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