Peer-to-Peer: Is Deviant Behavior the Norm on P2P File-Sharing Networks?

Hughes, Danny; Walkerdine, J.; Coulson, G.; Gibson, S.

doi:10.1109/mdso.2006.13

Cited by 37 publications

(47 citation statements)

References 6 publications

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“…For video analysis they use not only image features but also motion information [7]. Research related to child sex abuse in P2P networks is scarce,with few exceptions such as MAPAP [11], which focuses on the eDonkey network, or Huges et al [5], studying the Gnutella network. Liberatore et al [9] discussed legal issues involved in investigating child pornography in the Gnutella and BitTorrent networks.…”

Section: Introductionmentioning

confidence: 99%

Detecting Pedophile Activity in BitTorrent Networks

Rutgaizer

Shavitt

Vertman

et al. 2012

Passive and Active Measurement

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Abstract. The wide spread of Peer-to-Peer networks makes multimedia files available to users all around the world. However, Peer-to-Peer networks are often used to spread illegal material, while keeping the source of the data and the acquiring users anonymous. In this paper we analyze activity measurements in the BitTorrent network and examine child sex abuse activity through the Mininova web portal. We detect and characterize pedophilic material in the network, and also analyze different aspects of the abusers activity. We hope our results will help law enforcement teams detecting child molesters and tracking them down earlier.

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Section: Introductionmentioning

confidence: 99%

Detecting Pedophile Activity in BitTorrent Networks

Rutgaizer

Shavitt

Vertman

et al. 2012

Passive and Active Measurement

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“…Current research suggests that 90% of all material on P2P file sharing networks is copyrighted [9]. Likewise a recent study [6] showed that 1.6% of searches and 2.4% of searchresponses on the Gnutella P2P network relate to illegal sexual content such as images of child sexual abuse. These levels equate to hundreds of searches for illegal images per second.…”

Section: P2p File Sharingmentioning

confidence: 95%

“…Our study reuses tracing data collected and reported on in a previous study [6], however the analysis reported here is new and focuses specifically on child sexual abuse. We then describe an exploratory study involving the classification of emerging criminal terminology using natural language analysis.…”

Section: IIImentioning

confidence: 99%

“…Our previous research has shown that P2P file sharing networks, and specifically Gnutella, are a major vector for the distribution of illegal sexual material [6]. We now revisit our experiments on the Gnutella P2P file sharing network in order to specifically analyze the extent to which this system is used to distribute media related to child sexual abuse.…”

Section: Child Sexual Abuse Media Distribution On File Sharing Networkmentioning

confidence: 99%

“…For example, social networking sites have given rise to the phenomenon of 'cyber-stalking' [4] while chat applications have been used by paedophiles to support online victimisation, such as the 'grooming' of children [5]. Similarly, P2P file sharing systems have been implicated in both copyright infringement and the distribution of material related to child sexual abuse [6]. Digital communities, therefore, present two major and related challenges to law enforcement:…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Supporting Law Enforcement in Digital Communities through Natural Language Analysis

Hughes

Rayson

Walkerdine

et al.

Lecture Notes in Computer Science

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Recent years have seen an explosion in the number and scale of digital communities (e.g. peer-to-peer file sharing systems, chat applications and social networking sites). Unfortunately, digital communities are host to significant criminal activity including copyright infringement, identity theft and child sexual abuse. Combating this growing level of crime is problematic due to the ever increasing scale of today's digital communities. This paper presents an approach to provide automated support for the detection of child sexual abuse related activities in digital communities. Specifically, we analyze the characteristics of child sexual abuse media distribution in P2P file sharing networks and carry out an exploratory study to show that corpus-based natural language analysis may be used to automate the detection of this activity. We then give an overview of how this approach can be extended to police chat and social networking communities.

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Social Topology Analyzed

Borch

Andersen

Vognild

On the Move to Meaningful Internet Systems 2007: CoopIS, DOA, ODBASE, GADA, and IS

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It is an aspiring trend that Internet users not only consume, but also produce and share content. This leads to content of great diversity. Personalized navigation is an approach to correctly discover interesting content for the user. This navigation can be based on both search and recommendation systems.The Socialized.Net is a social Peer-to-Peer network infrastructure supporting personalized navigation. In this paper, a data trace of a popular file sharing site is analyzed and shown to have semantically close users. The data trace is further used for simulations in The Socialized.Net. Evidence is given that a fully distributed social network can be created based on traffic analysis. This can provide a powerful platform for personalized content navigation.

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Peer-to-Peer: Is Deviant Behavior the Norm on P2P File-Sharing Networks?

Cited by 37 publications

References 6 publications

Detecting Pedophile Activity in BitTorrent Networks

Detecting Pedophile Activity in BitTorrent Networks

Supporting Law Enforcement in Digital Communities through Natural Language Analysis

Social Topology Analyzed

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