139 research outputs found

    Finding Safety in Numbers with Secure Allegation Escrows

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    For fear of retribution, the victim of a crime may be willing to report it only if other victims of the same perpetrator also step forward. Common examples include 1) identifying oneself as the victim of sexual harassment, especially by a person in a position of authority or 2) accusing an influential politician, an authoritarian government, or ones own employer of corruption. To handle such situations, legal literature has proposed the concept of an allegation escrow: a neutral third-party that collects allegations anonymously, matches them against each other, and de-anonymizes allegers only after de-anonymity thresholds (in terms of number of co-allegers), pre-specified by the allegers, are reached. An allegation escrow can be realized as a single trusted third party; however, this party must be trusted to keep the identity of the alleger and content of the allegation private. To address this problem, this paper introduces Secure Allegation Escrows (SAE, pronounced "say"). A SAE is a group of parties with independent interests and motives, acting jointly as an escrow for collecting allegations from individuals, matching the allegations, and de-anonymizing the allegations when designated thresholds are reached. By design, SAEs provide a very strong property: No less than a majority of parties constituting a SAE can de-anonymize or disclose the content of an allegation without a sufficient number of matching allegations (even in collusion with any number of other allegers). Once a sufficient number of matching allegations exist, the join escrow discloses the allegation with the allegers' identities. We describe how SAEs can be constructed using a novel authentication protocol and a novel allegation matching and bucketing algorithm, provide formal proofs of the security of our constructions, and evaluate a prototype implementation, demonstrating feasibility in practice.Comment: To appear in NDSS 2020. New version includes improvements to writing and proof. The protocol is unchange

    Misbehaving TCP Receivers Can Cause Internet-Wide Congestion Collapse

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    An "optimistic" acknowledgment (OptAck) is an acknowledgment sent by a misbehaving client for a data segment that it has not received. Whereas previous work has focused on OptAck as a means to greedily improve end-to-end performance, we study OptAck exclusively as a denial of service attack. Specifically, an attacker sends optimistic acknowledgments to many victims in parallel, thereby amplifying its effective bandwidth by a factor of 30 million (worst case). Thus, even a relatively modest attacker can totally saturate the paths from many victims back to the attacker. Worse, a distributed network of compromised machines (``zombies'') can exploit this attack in parallel to bring about wide-spread, sustained congestion collapse. We implement this attack both in simulation and in a wide-area network, and show it severity both in terms of number of packets and total traffic generated. We engineer and implement a novel solution that does not require client or network modifications allowing for practical deployment. Additionally, we demonstrate the solution's efficiency on a real network

    Analysis of the NICE Application Layer Multicast Protocol

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    Application layer multicast protocols organize a set of hosts into an overlay tree for data delivery. Each host on the overlay peers with a subset of other hosts. Since application layer multicast relies only on an underlying unicast architecture, multiple copies of the same packet can be carried by a single physical link or node on the overlay. The stress at a link or node is defined as the number of identical copies of a packet carried by that link or node. Stretch is another important metric in application layer multicast, which measures the relative increase in delay incurred by the overlay path between pairs of members with respect to the direct unicast path. In this paper we study the NICE application layer multicast protocol to quantify and study the tradeoff between these two important metrics --- stress and stretch in scalably building application layer multicast paths. Also UMIACS-TR-2002-6

    Slurpie: A Cooperative Bulk Data Transfer Protocol

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    We present Slurpie: a peer-to-peer protocol for bulk data transfer. Slurpie is specifically designed to reduce client download times for large, popular files, and to reduce load on servers that serve these files. Slurpie employs a novel adaptive downloading strategy to increase client performance, and employs a randomized backoff strategy to precisely control load on the server. We describe a full implementation of the Slurpie protocol, and present results from both controlled localarea and wide-area testbeds. Our results show that Slurpie clients improve performance as the size of the network increases, and the server is completely insulated from large flash crowds entering the Slurpie network

    A Protocol for Scalable Application Layer Multicast

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    We describe a new application-layer multicast protocol that is specifically designed to scale to large groups. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can be used to produce a number of different data delivery trees with specific properties. On average, group members using our protocol maintain only a constant amount of state about other group members, and incur a constant amount of control overhead. We present extensive simulations of both our protocol and the Narada protocol over Internet-like topologies. Our results show that for groups of size 32 or more, we reduce control overhead by orders of magnitude, and link stress by 25%, while retaining similar end-to-end latencies and failure recovery properties

    A Security Infrastructure for Mobile Transactional Systems

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    In this paper, we present an infrastructure for providing secure transactional replication support for peer-to-peer, decentralized databases. We first describe how to effectively provide protection against external threats, malicious actions by servers not authorized to access data, using conventional cryp-tography-based mechanisms. We then classify and present algorithms that provide protection against internal threats, malicious actions by authenticated servers that misrepresent protocol-specific infor-mation. Our approach to handling internal threats uses both cryptographic techniques and modifica-tions to the update commit criteria. The techniques we propose are unique in that they not only enable a tradeoff between performance and the degree of tolerance to malicious servers, but also allow for indi-vidual servers to support non-uniform degrees of tolerance without adversely affecting the performance of the rest of the system. We investigate the cost of our security mechanisms in the context of Deno: a prototype object replica-tion system designed for use in mobile and weakly-connected environments. Experimental results reveal that protecting against internal threats comes at a cost, but the marginal cost for protecting against larger cliques of malicious insiders is generally low. Furthermore, comparison with a decentralized Read-One Write-All protocol shows that our approach performs significantly better under various workloads. (Also cross-referenced as UMIACS-TR-2000-59

    IP geolocation in metropolitan areas

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    BitTorrent is an Auction: Analyzing and Improving BitTorrent’s Incentives, in:

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    ABSTRACT Incentives play a crucial role in BitTorrent, motivating users to upload to others to achieve fast download times for all peers. Though long believed to be robust to strategic manipulation, recent work has empirically shown that BitTorrent does not provide its users incentive to follow the protocol. We propose an auction-based model to study and improve upon BitTorrent's incentives. The insight behind our model is that BitTorrent uses, not tit-for-tat as widely believed, but an auction to decide which peers to serve. Our model not only captures known, performance-improving strategies, it shapes our thinking toward new, effective strategies. For example, our analysis demonstrates, counter-intuitively, that BitTorrent peers have incentive to intelligently under-report what pieces of the file they have to their neighbors. We implement and evaluate a modification to BitTorrent in which peers reward one another with proportional shares of bandwidth. Within our game-theoretic model, we prove that a proportional-share client is strategy-proof. With experiments on PlanetLab, a local cluster, and live downloads, we show that a proportional-share unchoker yields faster downloads against BitTorrent and BitTyrant clients, and that underreporting pieces yields prolonged neighbor interest

    Efficient Peer-to-Peer Namespace Searches

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    In this paper we describe new methods for efficient and exact search (keyword and full-text) in distributed namespaces. Our methods can be used in conjunction with existing distributed lookup schemes, such as Distributed Hash Tables, and distributed directories. We describe how indexes for implementing distributed searches can be efficiently created, located, and stored. We describe techniques for creating approximate indexes that can be used to bound the space requirement at individual hosts; such techniques are particularly useful for full-text searches that may require a very large number of individual indexes to be created and maintained. Our methods use a new distributed data structure called the view tree. View trees can be used to efficiently cache and locate results from prior queries. We describe how view trees are created, and maintained. We present experimental results, using large namespaces and realistic data, showing that the techniques introduced in this paper can reduce search overheads (both network and processing costs) by more than an order of magnitude. (UMIACS-TR-2004-13
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