Attacking a Swarm with a Band of Liars: evaluating the impact of attacks on BitTorrent

Konrath, Marlom A.; Barcellos, Marinho P.; Mansilha, Rodrigo B.

doi:10.1109/p2p.2007.4343462

Cited by 6 publications

(6 citation statements)

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“…In an online social network (OSN) where users are associated with unique numeric IDs, uniform node sampling is performed by querying randomly generated IDs. In a P2P network like Bittorrent, uniform node sampling is performed by querying a tracker server [14]. In practice, however, these samples are expensive (resource-wise) operations (the ID space in an OSN, such as Facebook and MySpace, is large and sparse and tracker queries can be rate-limited [14]).…”

Section: Introductionmentioning

confidence: 99%

“…In a P2P network like Bittorrent, uniform node sampling is performed by querying a tracker server [14]. In practice, however, these samples are expensive (resource-wise) operations (the ID space in an OSN, such as Facebook and MySpace, is large and sparse and tracker queries can be rate-limited [14]). For instance, in MySpace we expect only 10% the IDs to belong to valid users [10], i.e., only one in every ten queries successfully finds a valid MySpace account.…”

Section: Introductionmentioning

confidence: 99%

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Improving Random Walk Estimation Accuracy with Uniform Restarts

Avrachenkov

Ribeiro

Towsley

2010

Algorithms and Models for the Web-Graph

152

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This work proposes and studies the properties of a hybrid sampling scheme that mixes independent uniform node sampling and random walk (RW)-based crawling. We show that our sampling method combines the strengths of both uniform and RW sampling while minimizing their drawbacks. In particular, our method increases the spectral gap of the random walk, and hence, accelerates convergence to the stationary distribution. The proposed method resembles PageRank but unlike PageRank preserves time-reversibility. Applying our hybrid RW to the problem of estimating degree distributions of graphs shows promising results. Key-words:

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving Random Walk Estimation Accuracy with Uniform Restarts

Avrachenkov

Ribeiro

Towsley

2010

Algorithms and Models for the Web-Graph

152

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“…Malicious peers will cheat the seeder and the tracker [3]. Figure 1 shows Sybil nodes can annoy participants with the following attacks.…”

Section: Threat Modelsmentioning

confidence: 99%

“…The original seeder hashes each block in the file with k hash functions, and marks the corresponding k bits in the filter. After processing all blocks, the seeder adds this B F ilter to the torrent metadata 3 . After obtaining the torrent file, leechers do not need to download it again when they rejoin the swarm.…”

Section: Golf Schemementioning

confidence: 99%

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Defending against Sybil Nodes in BitTorrent

Reeves

2011

Networking 2011

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Abstract. BitTorrent and its derivatives contribute a major portion of Internet traffic due to their simple and scalable operation. However, the lack of security mechanisms makes them vulnerable to attacks such as file piece pollution, connection slot consumption, and bandwidth exhaustion. These effects are made worse by the ability of attackers to manufacture new identities, or Sybil nodes, at will. The net effect of Sybil nodes and weak security leads to inefficient BitTorrent operation, or collapse. In this paper, we present defenses against threats from Sybil attackers in BitTorrent. A simple, direct reputation scheme called GOLF fosters peer cooperation to exclude potential attackers. Locality filtering tentatively identifies Sybil nodes based on patterns in IP addresses. Under the proposed scheme, Sybil attackers may still continue malicious behaviors, but their effect sharply decreases. Comparison to existing reputation models shows GOLF effectively detects and blocks potential attackers, despite false accusation.

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Securing BitTorrent using a new reputation-based trust management system

Sarjaz

Abbaspour

2012

Peer-to-Peer Netw. Appl.

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Attacking a Swarm with a Band of Liars: evaluating the impact of attacks on BitTorrent

Cited by 6 publications

References 0 publications

Improving Random Walk Estimation Accuracy with Uniform Restarts

Improving Random Walk Estimation Accuracy with Uniform Restarts

Defending against Sybil Nodes in BitTorrent

Securing BitTorrent using a new reputation-based trust management system

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