1,120 research outputs found
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
Graffiti Networks: A Subversive, Internet-Scale File Sharing Model
The proliferation of peer-to-peer (P2P) file sharing protocols is due to
their efficient and scalable methods for data dissemination to numerous users.
But many of these networks have no provisions to provide users with long term
access to files after the initial interest has diminished, nor are they able to
guarantee protection for users from malicious clients that wish to implicate
them in incriminating activities. As such, users may turn to supplementary
measures for storing and transferring data in P2P systems. We present a new
file sharing paradigm, called a Graffiti Network, which allows peers to harness
the potentially unlimited storage of the Internet as a third-party
intermediary. Our key contributions in this paper are (1) an overview of a
distributed system based on this new threat model and (2) a measurement of its
viability through a one-year deployment study using a popular web-publishing
platform. The results of this experiment motivate a discussion about the
challenges of mitigating this type of file sharing in a hostile network
environment and how web site operators can protect their resources
On Constructing Persistent Identifiers with Persistent Resolution Targets
Persistent Identifiers (PID) are the foundation referencing digital assets in
scientific publications, books, and digital repositories. In its realization,
PIDs contain metadata and resolving targets in form of URLs that point to data
sets located on the network. In contrast to PIDs, the target URLs are typically
changing over time; thus, PIDs need continuous maintenance -- an effort that is
increasing tremendously with the advancement of e-Science and the advent of the
Internet-of-Things (IoT). Nowadays, billions of sensors and data sets are
subject of PID assignment. This paper presents a new approach of embedding
location independent targets into PIDs that allows the creation of
maintenance-free PIDs using content-centric network technology and overlay
networks. For proving the validity of the presented approach, the Handle PID
System is used in conjunction with Magnet Link access information encoding,
state-of-the-art decentralized data distribution with BitTorrent, and Named
Data Networking (NDN) as location-independent data access technology for
networks. Contrasting existing approaches, no green-field implementation of PID
or major modifications of the Handle System is required to enable
location-independent data dissemination with maintenance-free PIDs.Comment: Published IEEE paper of the FedCSIS 2016 (SoFAST-WS'16) conference,
11.-14. September 2016, Gdansk, Poland. Also available online:
http://ieeexplore.ieee.org/document/7733372
Scalable Peer-to-Peer Streaming for Live Entertainment Content
We present a system for streaming live entertainment content over the Internet originating from a single source to a scalable number of consumers without resorting to centralized or provider-provisioned resources. The system creates a peer-to-peer overlay network, which attempts to optimize use of existing capacity to ensure quality of service, delivering low startup delay and lag in playout of the live content. There are three main aspects of our solution: first, a swarming mechanism that constructs an overlay topology for minimizing propagation delays from the source to end consumers; second, a distributed overlay anycast system that uses a location-based search algorithm for peers to quickly find the closest peers in a given stream; and finally, a novel incentive mechanism that encourages peers to donate capacity even when the user is not actively consuming content
Taxonomy of P2P Applications
Peer-to-peer (p2p) networks have gained immense popularity in recent years and the number of services they provide continuously rises. Where p2p-networks were formerly known as file-sharing networks, p2p is now also used for services like VoIP and IPTV. With so many different p2p applications and services the need for a taxonomy framework rises. This paper describes the available p2p applications grouped by the services they provide. A taxonomy framework is proposed to classify old and recent p2p applications based on their characteristics
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Mitigating the Effect of Free-Riders in BitTorrent using Trusted Agents
Even though Peer-to-Peer (P2P) systems present a cost-effective and scalable solution to content distribution, most entertainment, media and software, content providers continue to rely on expensive, centralized solutions such as Content Delivery Networks. One of the main reasons is that the current P2P systems cannot guarantee reasonable performance as they depend on the willingness of users to contribute bandwidth. Moreover, even systems like BitTorrent, which employ a tit-for-tat protocol to encourage fair bandwidth exchange between users, are prone to free-riding (i.e. peers that do not upload). Our experiments on PlanetLab extend previous research (e.g. LargeViewExploit, BitTyrant) demonstrating that such selfish behavior can seriously degrade the performance of regular users in many more scenarios beyond simple free-riding: we observed an overhead of up to 430% for 80% of free-riding identities easily generated by a small set of selfish users. To mitigate the effects of selfish users, we propose a new P2P architecture that classifies peers with the help of a small number of {\em trusted nodes} that we call Trusted Auditors (TAs). TAs participate in P2P download like regular clients and detect free-riding identities by observing their neighbors' behavior. Using TAs, we can separate compliant users into a separate service pool resulting in better performance. Furthermore, we show that TAs are more effective ensuring the performance of the system than a mere increase in bandwidth capacity: for 80\% of free-riding identities a single-TA system has a 6\% download time overhead while without the TA and three times the bandwidth capacity we measure a 100\% overhead
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