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BitTorrent Needs Psychiatric Guarantees: Quantifying How Vulnerable BitTorrent Swarms Are to Sybil Attacks
 

BitTorrent Needs Psychiatric Guarantees: Quantifying How Vulnerable BitTorrent Swarms Are to Sybil Attacks

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Apresentação realizada por Felipe Pontes no LADC'09. Pesquisa desenvolvida no Laboratório de Sistemas Distribuídos (LSD) - Universidade Federal de Campina Grande (UFCG)

Apresentação realizada por Felipe Pontes no LADC'09. Pesquisa desenvolvida no Laboratório de Sistemas Distribuídos (LSD) - Universidade Federal de Campina Grande (UFCG)

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    BitTorrent Needs Psychiatric Guarantees: Quantifying How Vulnerable BitTorrent Swarms Are to Sybil Attacks BitTorrent Needs Psychiatric Guarantees: Quantifying How Vulnerable BitTorrent Swarms Are to Sybil Attacks Presentation Transcript

    • BitTorrent Needs Psychiatric Guarantees: Quantifying How Vulnerable BitTorrent Swarms Are to Sybil Attacks
      Felipe Pontes
      Francisco Brasileiro
      Nazareno Andrade
      09/02/2009
    • Introduction
      BitTorrent Protocol
      Sybil Attacks
      Sybil Attacks in BitTorrent Systems
      Simulations
      Conclusions
      2
      Agenda
    • BitTorrent is one of the most popular content distribution protocols nowadays
      In BitTorrent she who donates more earns more
      Is it possible for someone to have a better download time than that of a collaborator?
      3
      Introduction
    • BitTorrent has a completely autonomous identification generation scheme
      Peers use a random mechanism to discover other peers
      Multiple identities to fool BitTorrent system sybil attack
      4
      Introduction
    • To evaluate the impact of sybil attacks in BitTorrent systems when an attacker is interested in increasing her utility
      5
      Goal
    • BitTorrentProtocol
      Distribution cost shared between peers
      Peers downloading a file (leechers) and peers that have already downloaded it (seeders) form a swarm
      Trackers help peers to discover other peers
      6
    • Based on a tit-for-tat strategy
      Peers who have higher upload rates probably will have higher download rates
      Connections used to make upload are called unchoked connections
      Periodically a peer chooses to whom she donates
      7
      BitTorrent Incentive Mechanism
    • A peer has not a whole system overview
      The peer might be choked by potential good partners for not having uploaded to them recently
      BitTorrent implements a periodic optimistic unchoking
      A leecher periodically unchokes randomly-choosen connections
      8
      BitTorrent Incentive Mechanism
    • An attacker associates multiple identities to herself in an attempt to fool the other entities
      Proper scenarios
      Spam
      Sensor networks
      Router overlays
      Online voting
      Peer-to-peer grids
      Resource sharing
      9
      SybilAttacks
    • Tracker flooded with sybil identities
      Attacker increases her number of connections
      Optimistic unchoking connections
      How many identities are needed?
      Mathematical model to help us to estimate:
      Number of identities
      How rapidly an attacker downloads a file when compared to a collaborator
      10
      SybilAttacks in BitTorrent Systems
    • General Peer-to-Peer Simulator (GPS)
      BitTorrent swarms simulations
      Changes in GPS to support sybil attacks simulations
      Each peer is online for a contiguous period
      Torrents from traces of BitTorrent usage derived from a community that shares files for free distribution
      11
      Simulations
    • 12
      Simulations
      Unfeasible simulations execution using all torrents
      GPS memory constraints
      A representative sample of torrents to be analyzed in depth
      Main parameters
      Seeders leaving rate ( )
      Leechers leaving rate ( )
      File size
      Download and upload peers bandwidth
    • Agglomerative Hierarchical Clustering process
      Similar torrents are merged in clusters
      Similarity measured as the average Euclidian distance of all torrents
      Clusters’ heterogeneity increases
      A rule of thumb to stop the merge:
      To follow the average level of cluster heterogeneity on every step
      To stop the process just before the merges start increasing heterogeneity too rapidly
      13
      TorrentsClustering
    • 14
      TorrentsClustering
    • TorrentsClustering
      14 clusters
      7 non-representative clusters (only 1 or 2 torrents each)
      1 made up of a torrent too similar to other clusters
      1 made up of a torrent on which peers stay online for very little time
      5 clusters selected
      15
    • RepresentativeTorrents
      For each cluster we selected one representative torrent
      The torrent closest to the Euclidian center of cluster
      16
      Characteristics of torrents
    • 3 distinct attack times
      Start of the torrent (t0)
      An attacker wants the file as soon as it is published
      Maximum number of leechers (tc)
      High resource contention
      Number of seeders overlaps the number of leechers (ts)
      Low resource contention
      17
      ScenariosofSimulations
    • 3 versions of each torrent
      All leechers act correctly
      One leecher replaced by the sybil attacker
      One leecher replaced by a free rider
      Sybil attack is effective if the attacker download average rate is equal to or higher than leecher rate
      The attacker is not incurring in the cost of uploading to the system
      18
      ScenariosofSimulations
    • Results considering 95% of confidence level and 5% of error
      Average download rates increase with the attack starting time
      Being a correct leecher was better than being a free rider
      Performing a sybil attack was better than being a free rider
      19
      Simulations’ Results
    • Only a small number of identities is needed for an attack to be effective
      In 4 out of the 5 representative torrents simulated the attacker needed only 8 identities
      In all torrents simulated the attacker could succeed with at most 130 identities
      Mathematical model is considerably accurate
      Only for 4 scenarios the attack was not effective
      Large populations of peers at the time of the attack
      20
      Simulations’ Results
    • Simulations’ Results
      21
      Download average rates to torrent of cluster 4
    • Simulations’ Results
      22
      Download average rates for tenfold increase of identities of torrent of cluster 4
    • It is possible to perform a sybil attack in BitTorrent
      When there is high resource contention the attack was not successful in some scenarios
      To increase the number of identities can change the attack result
      Greedy attackers might cause the death of torrents
      Mechanisms to address sybil attacks in BitTorrent
      23
      Conclusions
    • To improve the mathematical model
      To investigate probabilistic optimistic unchoking as a strategy to mitigate a sybil attack
      To validate results presented in this work experimentally using real torrents
      To consider the evolutionary dynamics of sybil attack strategies
      24
      Future Works
    • Thank You!
      Felipe Pontes
      felipep@lsd.ufcg.edu.br
      This work was developed in collaboration with HP Brasil P&D